WorldWideScience

Sample records for network analysis demonstrated

  1. Design and analysis of electrical energy storage demonstration projects on UK distribution networks

    International Nuclear Information System (INIS)

    Lyons, P.F.; Wade, N.S.; Jiang, T.; Taylor, P.C.; Hashiesh, F.; Michel, M.; Miller, D.

    2015-01-01

    Highlights: • Results of an EES system demonstration project carried out in the UK. • Approaches to the design of trials for EES and observation on their application. • A formalised methodology for analysis of smart grids trials. • Validated models of energy storage. • Capability of EES to connect larger quantities of heat pumps and PV is evaluated. - Abstract: The UK government’s CO 2 emissions targets will require electrification of much of the country’s infrastructure with low carbon technologies such as photovoltaic panels, electric vehicles and heat pumps. The large scale proliferation of these technologies will necessitate major changes to the planning and operation of distribution networks. Distribution network operators are trialling electrical energy storage (EES) across their networks to increase their understanding of the contribution that it can make to enable the expected paradigm shift in generation and consumption of electricity. In order to evaluate a range of applications for EES, including voltage control and power flow management, installations have taken place at various distribution network locations and voltage levels. This article reports on trial design approaches and their application to a UK trial of an EES system to ensure broad applicability of the results. Results from these trials of an EES system, low carbon technologies and trial distribution networks are used to develop validated power system models. These models are used to evaluate, using a formalised methodology, the impact that EES could have on the design and operation of future distribution networks

  2. Weaving the native web: using social network analysis to demonstrate the value of a minority career development program.

    Science.gov (United States)

    Buchwald, Dedra; Dick, Rhonda Wiegman

    2011-06-01

    American Indian and Alaska Native scientists are consistently among the most underrepresented minority groups in health research. The authors used social network analysis (SNA) to evaluate the Native Investigator Development Program (NIDP), a career development program for junior Native researchers established as a collaboration between the University of Washington and the University of Colorado Denver. The study focused on 29 trainees and mentors who participated in the NIDP. Data were collected on manuscripts and grant proposals produced by participants from 1998 to 2007. Information on authorship of manuscripts and collaborations on grant applications was used to conduct social network analyses with three measures of centrality and one measure of network reach. Both visual and quantitative analyses were performed. Participants in the NIDP collaborated on 106 manuscripts and 83 grant applications. Although three highly connected individuals, with critical and central roles in the program, accounted for much of the richness of the network, both current core faculty and "graduates" of the program were heavily involved in collaborations on manuscripts and grants. This study's innovative application of SNA demonstrates that collaborative relationships can be an important outcome of career development programs for minority investigators and that an analysis of these relationships can provide a more complete assessment of the value of such programs.

  3. No study left behind: a network meta-analysis in non-small-cell lung cancer demonstrating the importance of considering all relevant data.

    Science.gov (United States)

    Hawkins, Neil; Scott, David A; Woods, Beth S; Thatcher, Nicholas

    2009-09-01

    To demonstrate the importance of considering all relevant indirect data in a network meta-analysis of treatments for non-small-cell lung cancer (NSCLC). A recent National Institute for Health and Clinical Excellence appraisal focussed on the indirect comparison of docetaxel with erlotinib in second-line treatment of NSCLC based on trials including a common comparator. We compared the results of this analysis to a network meta-analysis including other trials that formed a network of evidence. We also examined the importance of allowing for the correlations between the estimated treatment effects that can arise when analysing such networks. The analysis of the restricted network including only trials of docetaxel and erlotinib linked via the common placebo comparator produced an estimated mean hazard ratio (HR) for erlotinib compared with docetaxel of 1.55 (95% confidence interval [CI] 0.72-2.97). In contrast, the network meta-analysis produced an estimated HR for erlotinib compared with docetaxel of 0.83 (95% CI 0.65-1.06). Analyzing the wider network improved the precision of estimated treatment effects, altered their rankings and also allowed further treatments to be compared. Some of the estimated treatment effects from the wider network were highly correlated. This empirical example shows the importance of considering all potentially relevant data when comparing treatments. Care should therefore be taken to consider all relevant information, including correlations induced by the network of trial data, when comparing treatments.

  4. [Text mining, a method for computer-assisted analysis of scientific texts, demonstrated by an analysis of author networks].

    Science.gov (United States)

    Hahn, P; Dullweber, F; Unglaub, F; Spies, C K

    2014-06-01

    Searching for relevant publications is becoming more difficult with the increasing number of scientific articles. Text mining as a specific form of computer-based data analysis may be helpful in this context. Highlighting relations between authors and finding relevant publications concerning a specific subject using text analysis programs are illustrated graphically by 2 performed examples. © Georg Thieme Verlag KG Stuttgart · New York.

  5. Demonstration of statistical approaches to identify component's ageing by operational data analysis-A case study for the ageing PSA network

    International Nuclear Information System (INIS)

    Rodionov, Andrei; Atwood, Corwin L.; Kirchsteiger, Christian; Patrik, Milan

    2008-01-01

    The paper presents some results of a case study on 'Demonstration of statistical approaches to identify the component's ageing by operational data analysis', which was done in the frame of the EC JRC Ageing PSA Network. Several techniques: visual evaluation, nonparametric and parametric hypothesis tests, were proposed and applied in order to demonstrate the capacity, advantages and limitations of statistical approaches to identify the component's ageing by operational data analysis. Engineering considerations are out of the scope of the present study

  6. Edison Demonstration of Smallsat Networks (EDSN)

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA's Edison Demonstration of SmallSat Networks (EDSN) mission will launch and deploy a group of eight cubesats into a loose formation approximately 250 miles (400...

  7. Information Operations Innovation Network (IOIN) Demonstration

    National Research Council Canada - National Science Library

    Choo, Vic; Scheiderich, Louis

    2006-01-01

    ...; and Supplement existing/future network defense tools with additional capabilities. The actual software packages used for this effort include VIAasst, VisAlert, Flexviewer, Event Correlation for Cyber Attack Recognition (ECCARS...

  8. Ecological network analysis: network construction

    NARCIS (Netherlands)

    Fath, B.D.; Scharler, U.M.; Ulanowicz, R.E.; Hannon, B.

    2007-01-01

    Ecological network analysis (ENA) is a systems-oriented methodology to analyze within system interactions used to identify holistic properties that are otherwise not evident from the direct observations. Like any analysis technique, the accuracy of the results is as good as the data available, but

  9. Hardware demonstration of high-speed networks for satellite applications.

    Energy Technology Data Exchange (ETDEWEB)

    Donaldson, Jonathon W.; Lee, David S.

    2008-09-01

    This report documents the implementation results of a hardware demonstration utilizing the Serial RapidIO{trademark} and SpaceWire protocols that was funded by Sandia National Laboratories (SNL's) Laboratory Directed Research and Development (LDRD) office. This demonstration was one of the activities in the Modeling and Design of High-Speed Networks for Satellite Applications LDRD. This effort has demonstrated the transport of application layer packets across both RapidIO and SpaceWire networks to a common downlink destination using small topologies comprised of commercial-off-the-shelf and custom devices. The RapidFET and NEX-SRIO debug and verification tools were instrumental in the successful implementation of the RapidIO hardware demonstration. The SpaceWire hardware demonstration successfully demonstrated the transfer and routing of application data packets between multiple nodes and also was able reprogram remote nodes using configuration bitfiles transmitted over the network, a key feature proposed in node-based architectures (NBAs). Although a much larger network (at least 18 to 27 nodes) would be required to fully verify the design for use in a real-world application, this demonstration has shown that both RapidIO and SpaceWire are capable of routing application packets across a network to a common downlink node, illustrating their potential use in real-world NBAs.

  10. Sensor Network Demonstration for In Situ Decommissioning - 13332

    Energy Technology Data Exchange (ETDEWEB)

    Lagos, L.; Varona, J.; Awwad, A. [Applied Research Center, Florida International University, 10555 West Flagler Street, Suite 2100, Miami, FL 33174 (United States); Rivera, J.; McGill, J. [Department of Energy - DOE, Environmental Management Office (United States)

    2013-07-01

    ensure that the individual sensors would be immobilized during the grout pouring activities, a set of nine sensor racks were designed. The 270 sensors provided by Idaho National Laboratory (INL), Mississippi State University (MSU), University of Houston (UH), and University of South Carolina (USC) were secured to these racks based on predetermined locations. Once sensor racks were installed inside the test cube, connected and debugged, approximately 32 cubic yards of special grout material was used to entomb the sensors. MSU provided and demonstrated four types of fiber loop ring-down (FLR) sensors for detection of water, temperature, cracks, and movement of fluids. INL provided and demonstrated time differenced 3D electrical resistivity tomography (ERT), advanced tensiometers for moisture content, and thermocouples for temperature measurements. University of Houston provided smart aggregate (SA) sensors, which detect crack severity and water presence. An additional UH sensor system demonstrated was a Fiber Bragg Grating (FBG) fiber optic system measuring strain, presence of water, and temperature. USC provided a system which measured acoustic emissions during cracking, as well as temperature and pH sensors. All systems were connected to a Sensor Remote Access System (SRAS) data networking and collection system designed, developed and provided by FIU. The purpose of SRAS was to collect and allow download of the raw sensor data from all the sensor system, as well as allow upload of the processed data and any analysis reports and graphs. All this information was made available to the research teams via the Deactivation and Decommissioning Knowledge Management and Information Tool (D and D KM-IT). As a current research effort, FIU is performing an energy analysis, and transferring several sensor systems to a Photovoltaic (PV) System to continuously monitor energy consumption parameters and overall power demands. Also, One final component of this research is focusing on

  11. Experimental demonstration of SCMA-OFDM for passive optical network

    Science.gov (United States)

    Lin, Bangjiang; Tang, Xuan; Shen, Xiaohuan; Zhang, Min; Lin, Chun; Ghassemlooy, Zabih

    2017-12-01

    We introduces a novel architecture for next generation passive optical network (PON) based on the employment of sparse code multiple access (SCMA) combined with orthogonal frequency division multiplexing (OFDM) modulation, in which the binary data is directly encoded to multi-dimensional codewords and then spread over OFDM subcarriers. The feasibility of SCMA-OFDM-PON is verified with experimental demonstration. We show that the SCMA-OFDM offers 150% overloading gain in the number of optical network units compared with the orthogonal frequency division multiplexing access.

  12. Secure, Mobile, Wireless Network Technology Designed, Developed, and Demonstrated

    Science.gov (United States)

    Ivancic, William D.; Paulsen, Phillip E.

    2004-01-01

    The inability to seamlessly disseminate data securely over a high-integrity, wireless broadband network has been identified as a primary technical barrier to providing an order-of-magnitude increase in aviation capacity and safety. Secure, autonomous communications to and from aircraft will enable advanced, automated, data-intensive air traffic management concepts, increase National Air Space (NAS) capacity, and potentially reduce the overall cost of air travel operations. For the first time ever, secure, mobile, network technology was designed, developed, and demonstrated with state-ofthe- art protocols and applications by a diverse, cooperative Government-industry team led by the NASA Glenn Research Center. This revolutionary technology solution will make fundamentally new airplane system capabilities possible by enabling secure, seamless network connections from platforms in motion (e.g., cars, ships, aircraft, and satellites) to existing terrestrial systems without the need for manual reconfiguration. Called Mobile Router, the new technology autonomously connects and configures networks as they traverse from one operating theater to another. The Mobile Router demonstration aboard the Neah Bay, a U.S. Coast Guard vessel stationed in Cleveland, Ohio, accomplished secure, seamless interoperability of mobile network systems across multiple domains without manual system reconfiguration. The Neah Bay was chosen because of its low cost and communications mission similarity to low-Earth-orbiting satellite platforms. This technology was successfully advanced from technology readiness level (TRL) 2 (concept and/or application formation) to TRL 6 (system model or prototype demonstration in a relevant environment). The secure, seamless interoperability offered by the Mobile Router and encryption device will enable several new, vehicle-specific and systemwide technologies to perform such things as remote, autonomous aircraft performance monitoring and early detection and

  13. Communication Network Analysis Methods.

    Science.gov (United States)

    Farace, Richard V.; Mabee, Timothy

    This paper reviews a variety of analytic procedures that can be applied to network data, discussing the assumptions and usefulness of each procedure when applied to the complexity of human communication. Special attention is paid to the network properties measured or implied by each procedure. Factor analysis and multidimensional scaling are among…

  14. Network analysis applications in hydrology

    Science.gov (United States)

    Price, Katie

    2017-04-01

    Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

  15. Environmental analysis for pipeline gas demonstration plants

    Energy Technology Data Exchange (ETDEWEB)

    Stinton, L.H.

    1978-09-01

    The Department of Energy (DOE) has implemented programs for encouraging the development and commercialization of coal-related technologies, which include coal gasification demonstration-scale activities. In support of commercialization activities the Environmental Analysis for Pipeline Gas Demonstration Plants has been prepared as a reference document to be used in evaluating potential environmental and socioeconomic effects from construction and operation of site- and process-specific projects. Effluents and associated impacts are identified for six coal gasification processes at three contrasting settings. In general, impacts from construction of a high-Btu gas demonstration plant are similar to those caused by the construction of any chemical plant of similar size. The operation of a high-Btu gas demonstration plant, however, has several unique aspects that differentiate it from other chemical plants. Offsite development (surface mining) and disposal of large quantities of waste solids constitute important sources of potential impact. In addition, air emissions require monitoring for trace metals, polycyclic aromatic hydrocarbons, phenols, and other emissions. Potential biological impacts from long-term exposure to these emissions are unknown, and additional research and data analysis may be necessary to determine such effects. Possible effects of pollutants on vegetation and human populations are discussed. The occurrence of chemical contaminants in liquid effluents and the bioaccumulation of these contaminants in aquatic organisms may lead to adverse ecological impact. Socioeconomic impacts are similar to those from a chemical plant of equivalent size and are summarized and contrasted for the three surrogate sites.

  16. Demonstration sensitivity analysis for RADTRAN III

    International Nuclear Information System (INIS)

    Neuhauser, K.S.; Reardon, P.C.

    1986-10-01

    A demonstration sensitivity analysis was performed to: quantify the relative importance of 37 variables to the total incident free dose; assess the elasticity of seven dose subgroups to those same variables; develop density distributions for accident dose to combinations of accident data under wide-ranging variations; show the relationship between accident consequences and probabilities of occurrence; and develop limits for the variability of probability consequence curves

  17. EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

    Directory of Open Access Journals (Sweden)

    Kumari Sonal Choudhary

    2016-06-01

    Full Text Available Epithelial to mesenchymal transition (EMT is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR, are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E and mesenchymal (EGFR_M networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

  18. EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

    Science.gov (United States)

    Choudhary, Kumari Sonal; Rohatgi, Neha; Halldorsson, Skarphedinn; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

    2016-06-01

    Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

  19. Google matrix analysis of directed networks

    Science.gov (United States)

    Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

    2015-10-01

    In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

  20. Network performance analysis

    CERN Document Server

    Bonald, Thomas

    2013-01-01

    The book presents some key mathematical tools for the performance analysis of communication networks and computer systems.Communication networks and computer systems have become extremely complex. The statistical resource sharing induced by the random behavior of users and the underlying protocols and algorithms may affect Quality of Service.This book introduces the main results of queuing theory that are useful for analyzing the performance of these systems. These mathematical tools are key to the development of robust dimensioning rules and engineering methods. A number of examples i

  1. Experimental demonstrations of all-optical networking functions for WDM optical networks

    Science.gov (United States)

    Gurkan, Deniz

    The deployment of optical networks will enable high capacity links between users but will introduce the problems associated with transporting and managing more channels. Many network functions should be implemented in optical domain; main reasons are: to avoid electronic processing bottlenecks, to achieve data-format and data-rate independence, to provide reliable and cost efficient control and management information, to simultaneously process multiple wavelength channel operation for wavelength division multiplexed (WDM) optical networks. The following novel experimental demonstrations of network functions in the optical domain are presented: Variable-bit-rate recognition of the header information in a data packet. The technique is reconfigurable for different header sequences and uses optical correlators as look-up tables. The header is processed and a signal is sent to the switch for a series of incoming data packets at 155 Mb/s, 622 Mb/s, and 2.5 Gb/s in a reconfigurable network. Simultaneous optical time-slot-interchange and wavelength conversion of the bits in a 2.5-Gb/s data stream to achieve a reconfigurable time/wavelength switch. The technique uses difference-frequency-generation (DFG) for wavelength conversion and fiber Bragg gratings (FBG) as wavelength-dependent optical time buffers. The WDM header recognition module simultaneously recognizing two header bits on each of two 2.5-Gbit/s WDM packet streams. The module is tunable to enable reconfigurable look-up tables. Simultaneous and independent label swapping and wavelength conversion of two WDM channels for a multi-protocol label switching (MPLS) network. Demonstration of label swapping of distinct 8-bit-long labels for two WDM data channels is presented. Two-dimensional code conversion module for an optical code-division multiple-access (O-CDMA) local area network (LAN) system. Simultaneous wavelength conversion and time shifting is achieved to enable flexible code conversion and increase code re

  2. Network systems security analysis

    Science.gov (United States)

    Yilmaz, Ä.°smail

    2015-05-01

    Network Systems Security Analysis has utmost importance in today's world. Many companies, like banks which give priority to data management, test their own data security systems with "Penetration Tests" by time to time. In this context, companies must also test their own network/server systems and take precautions, as the data security draws attention. Based on this idea, the study cyber-attacks are researched throughoutly and Penetration Test technics are examined. With these information on, classification is made for the cyber-attacks and later network systems' security is tested systematically. After the testing period, all data is reported and filed for future reference. Consequently, it is found out that human beings are the weakest circle of the chain and simple mistakes may unintentionally cause huge problems. Thus, it is clear that some precautions must be taken to avoid such threats like updating the security software.

  3. Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network

    Science.gov (United States)

    Bhatia, Udit; Kumar, Devashish; Kodra, Evan; Ganguly, Auroop R.

    2015-01-01

    The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general. PMID:26536227

  4. Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network.

    Science.gov (United States)

    Bhatia, Udit; Kumar, Devashish; Kodra, Evan; Ganguly, Auroop R

    2015-01-01

    The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general.

  5. Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network.

    Directory of Open Access Journals (Sweden)

    Udit Bhatia

    Full Text Available The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general.

  6. Review Essay: Does Qualitative Network Analysis Exist?

    Directory of Open Access Journals (Sweden)

    Rainer Diaz-Bone

    2007-01-01

    Full Text Available Social network analysis was formed and established in the 1970s as a way of analyzing systems of social relations. In this review the theoretical-methodological standpoint of social network analysis ("structural analysis" is introduced and the different forms of social network analysis are presented. Structural analysis argues that social actors and social relations are embedded in social networks, meaning that action and perception of actors as well as the performance of social relations are influenced by the network structure. Since the 1990s structural analysis has integrated concepts such as agency, discourse and symbolic orientation and in this way structural analysis has opened itself. Since then there has been increasing use of qualitative methods in network analysis. They are used to include the perspective of the analyzed actors, to explore networks, and to understand network dynamics. In the reviewed book, edited by Betina HOLLSTEIN and Florian STRAUS, the twenty predominantly empirically orientated contributions demonstrate the possibilities of combining quantitative and qualitative methods in network analyses in different research fields. In this review we examine how the contributions succeed in applying and developing the structural analysis perspective, and the self-positioning of "qualitative network analysis" is evaluated. URN: urn:nbn:de:0114-fqs0701287

  7. Analysis of computer networks

    CERN Document Server

    Gebali, Fayez

    2015-01-01

    This textbook presents the mathematical theory and techniques necessary for analyzing and modeling high-performance global networks, such as the Internet. The three main building blocks of high-performance networks are links, switching equipment connecting the links together, and software employed at the end nodes and intermediate switches. This book provides the basic techniques for modeling and analyzing these last two components. Topics covered include, but are not limited to: Markov chains and queuing analysis, traffic modeling, interconnection networks and switch architectures and buffering strategies.   ·         Provides techniques for modeling and analysis of network software and switching equipment; ·         Discusses design options used to build efficient switching equipment; ·         Includes many worked examples of the application of discrete-time Markov chains to communication systems; ·         Covers the mathematical theory and techniques necessary for ana...

  8. Reliability demonstration test planning using bayesian analysis

    International Nuclear Information System (INIS)

    Chandran, Senthil Kumar; Arul, John A.

    2003-01-01

    In Nuclear Power Plants, the reliability of all the safety systems is very critical from the safety viewpoint and it is very essential that the required reliability requirements be met while satisfying the design constraints. From practical experience, it is found that the reliability of complex systems such as Safety Rod Drive Mechanism is of the order of 10 -4 with an uncertainty factor of 10. To demonstrate the reliability of such systems is prohibitive in terms of cost and time as the number of tests needed is very large. The purpose of this paper is to develop a Bayesian reliability demonstrating testing procedure for exponentially distributed failure times with gamma prior distribution on the failure rate which can be easily and effectively used to demonstrate component/subsystem/system reliability conformance to stated requirements. The important questions addressed in this paper are: With zero failures, how long one should perform the tests and how many components are required to conclude with a given degree of confidence, that the component under test, meets the reliability requirement. The procedure is explained with an example. This procedure can also be extended to demonstrate with more number of failures. The approach presented is applicable for deriving test plans for demonstrating component failure rates of nuclear power plants, as the failure data for similar components are becoming available in existing plants elsewhere. The advantages of this procedure are the criterion upon which the procedure is based is simple and pertinent, the fitting of the prior distribution is an integral part of the procedure and is based on the use of information regarding two percentiles of this distribution and finally, the procedure is straightforward and easy to apply in practice. (author)

  9. Experimental demonstration of IDMA-OFDM for passive optical network

    Science.gov (United States)

    Lin, Bangjiang; Tang, Xuan; Li, Yiwei; Zhang, Min; Lin, Chun; Ghassemlooy, Zabih

    2017-11-01

    We present interleave division multiple access (IDMA) scheme combined with orthogonal frequency division multiplexing (OFDM) for passive optical network, which offers improved transmission performance and good chromatic dispersion tolerance. The interleavers are employed to separate different users and the generated chips are modulated on OFDM subcarriers. The feasibility of IDMA-OFDM-PON is experimentally verified with a bitrate of 3.3 Gb/s per user. Compared with OFDMA, IDMA-OFDM offers 8 and 6 dB gains in term of receiver sensitivity in the cases of 2 and 4 users, respectively.

  10. Structural Analysis of Complex Networks

    CERN Document Server

    Dehmer, Matthias

    2011-01-01

    Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science,

  11. Multifractal analysis of complex networks

    International Nuclear Information System (INIS)

    Wang Dan-Ling; Yu Zu-Guo; Anh V

    2012-01-01

    Complex networks have recently attracted much attention in diverse areas of science and technology. Many networks such as the WWW and biological networks are known to display spatial heterogeneity which can be characterized by their fractal dimensions. Multifractal analysis is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we introduce a new box-covering algorithm for multifractal analysis of complex networks. This algorithm is used to calculate the generalized fractal dimensions D q of some theoretical networks, namely scale-free networks, small world networks, and random networks, and one kind of real network, namely protein—protein interaction networks of different species. Our numerical results indicate the existence of multifractality in scale-free networks and protein—protein interaction networks, while the multifractal behavior is not clear-cut for small world networks and random networks. The possible variation of D q due to changes in the parameters of the theoretical network models is also discussed. (general)

  12. Network Analysis, Architecture, and Design

    CERN Document Server

    McCabe, James D

    2007-01-01

    Traditionally, networking has had little or no basis in analysis or architectural development, with designers relying on technologies they are most familiar with or being influenced by vendors or consultants. However, the landscape of networking has changed so that network services have now become one of the most important factors to the success of many third generation networks. It has become an important feature of the designer's job to define the problems that exist in his network, choose and analyze several optimization parameters during the analysis process, and then prioritize and evalua

  13. Network topology analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Kalb, Jeffrey L.; Lee, David S.

    2008-01-01

    Emerging high-bandwidth, low-latency network technology has made network-based architectures both feasible and potentially desirable for use in satellite payload architectures. The selection of network topology is a critical component when developing these multi-node or multi-point architectures. This study examines network topologies and their effect on overall network performance. Numerous topologies were reviewed against a number of performance, reliability, and cost metrics. This document identifies a handful of good network topologies for satellite applications and the metrics used to justify them as such. Since often multiple topologies will meet the requirements of the satellite payload architecture under development, the choice of network topology is not easy, and in the end the choice of topology is influenced by both the design characteristics and requirements of the overall system and the experience of the developer.

  14. Artificial Neural Network Analysis System

    Science.gov (United States)

    2001-02-27

    Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

  15. Applications of social media and social network analysis

    CERN Document Server

    Kazienko, Przemyslaw

    2015-01-01

    This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to commun

  16. Waste Energy Recovery from Natural Gas Distribution Network: CELSIUS Project Demonstrator in Genoa

    Directory of Open Access Journals (Sweden)

    Davide Borelli

    2015-12-01

    Full Text Available Increasing energy efficiency by the smart recovery of waste energy is the scope of the CELSIUS Project (Combined Efficient Large Scale Integrated Urban Systems. The CELSIUS consortium includes a world-leading partnership of outstanding research, innovation and implementation organizations, and gather competence and excellence from five European cities with complementary baseline positions regarding the sustainable use of energy: Cologne, Genoa, Gothenburg, London, and Rotterdam. Lasting four-years and coordinated by the City of Gothenburg, the project faces with an holistic approach technical, economic, administrative, social, legal and political issues concerning smart district heating and cooling, aiming to establish best practice solutions. This will be done through the implementation of twelve new high-reaching demonstration projects, which cover the most major aspects of innovative urban heating and cooling for a smart city. The Genoa demonstrator was designed in order to recover energy from the pressure drop between the main supply line and the city natural gas network. The potential mechanical energy is converted to electricity by a turboexpander/generator system, which has been integrated in a combined heat and power plant to supply a district heating network. The performed energy analysis assessed natural gas saving and greenhouse gas reduction achieved through the smart systems integration.

  17. Computational Social Network Analysis

    CERN Document Server

    Hassanien, Aboul-Ella

    2010-01-01

    Presents insight into the social behaviour of animals (including the study of animal tracks and learning by members of the same species). This book provides web-based evidence of social interaction, perceptual learning, information granulation and the behaviour of humans and affinities between web-based social networks

  18. Advanced Modulation Formats in Cognitive Optical Networks: EU project CHRON Demonstration

    DEFF Research Database (Denmark)

    Borkowski, Robert; Caballero Jambrina, Antonio; Klonidis, Dimitris

    2014-01-01

    We demonstrate real-time path establishment and switching of coherent modulation formats (QPSK, 16QAM) within an optical network driven by cognitive algorithms. Cognition aims at autonomous configuration optimization to satisfy quality of transmission requirements.......We demonstrate real-time path establishment and switching of coherent modulation formats (QPSK, 16QAM) within an optical network driven by cognitive algorithms. Cognition aims at autonomous configuration optimization to satisfy quality of transmission requirements....

  19. Field and long-term demonstration of a wide area quantum key distribution network.

    Science.gov (United States)

    Wang, Shuang; Chen, Wei; Yin, Zhen-Qiang; Li, Hong-Wei; He, De-Yong; Li, Yu-Hu; Zhou, Zheng; Song, Xiao-Tian; Li, Fang-Yi; Wang, Dong; Chen, Hua; Han, Yun-Guang; Huang, Jing-Zheng; Guo, Jun-Fu; Hao, Peng-Lei; Li, Mo; Zhang, Chun-Mei; Liu, Dong; Liang, Wen-Ye; Miao, Chun-Hua; Wu, Ping; Guo, Guang-Can; Han, Zheng-Fu

    2014-09-08

    A wide area quantum key distribution (QKD) network deployed on communication infrastructures provided by China Mobile Ltd. is demonstrated. Three cities and two metropolitan area QKD networks were linked up to form the Hefei-Chaohu-Wuhu wide area QKD network with over 150 kilometers coverage area, in which Hefei metropolitan area QKD network was a typical full-mesh core network to offer all-to-all interconnections, and Wuhu metropolitan area QKD network was a representative quantum access network with point-to-multipoint configuration. The whole wide area QKD network ran for more than 5000 hours, from 21 December 2011 to 19 July 2012, and part of the network stopped until last December. To adapt to the complex and volatile field environment, the Faraday-Michelson QKD system with several stability measures was adopted when we designed QKD devices. Through standardized design of QKD devices, resolution of symmetry problem of QKD devices, and seamless switching in dynamic QKD network, we realized the effective integration between point-to-point QKD techniques and networking schemes.

  20. Direct2Experts: a pilot national network to demonstrate interoperability among research-networking platforms

    OpenAIRE

    Weber, Griffin M; Barnett, William; Conlon, Mike; Eichmann, David; Kibbe, Warren; Falk-Krzesinski, Holly; Halaas, Michael; Johnson, Layne; Meeks, Eric; Mitchell, Donald; Schleyer, Titus; Stallings, Sarah; Warden, Michael; Kahlon, Maninder

    2011-01-01

    Research-networking tools use data-mining and social networking to enable expertise discovery, matchmaking and collaboration, which are important facets of team science and translational research. Several commercial and academic platforms have been built, and many institutions have deployed these products to help their investigators find local collaborators. Recent studies, though, have shown the growing importance of multiuniversity teams in science. Unfortunately, the lack of a standard dat...

  1. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

    Directory of Open Access Journals (Sweden)

    Kim Hyun

    2011-12-01

    Full Text Available Abstract Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

  2. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

    Science.gov (United States)

    Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

    2011-01-01

    Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

  3. Analysis of neural networks

    CERN Document Server

    Heiden, Uwe

    1980-01-01

    The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica­ ted throughout the text. However, they are not explored in de­ tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev­ els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be­ havior of neurons or neuron pools. In this respect the essay is writt...

  4. Transmission analysis in WDM networks

    DEFF Research Database (Denmark)

    Rasmussen, Christian Jørgen

    1999-01-01

    This thesis describes the development of a computer-based simulator for transmission analysis in optical wavelength division multiplexing networks. A great part of the work concerns fundamental optical network simulator issues. Among these issues are identification of the versatility and user...... the different component models are invoked during the simulation of a system. A simple set of rules which makes it possible to simulate any network architectures is laid down. The modelling of the nonlinear fibre and the optical receiver is also treated. The work on the fibre concerns the numerical solution...

  5. Modular analysis of biological networks.

    Science.gov (United States)

    Kaltenbach, Hans-Michael; Stelling, Jörg

    2012-01-01

    The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

  6. Demonstration of Hydrogen Energy Network and Fuel Cells in Residential Homes

    International Nuclear Information System (INIS)

    Hirohisa Aki; Tetsuhiko Maeda; Itaru Tamura; Akeshi Kegasa; Yoshiro Ishikawa; Ichiro Sugimoto; Itaru Ishii

    2006-01-01

    The authors proposed the setting up of an energy interchange system by establishing energy networks of electricity, hot water, and hydrogen in residential homes. In such networks, some homes are equipped with fuel cell stacks, fuel processors, hydrogen storage devices, and large storage tanks for hot water. The energy network enables the flexible operation of the fuel cell stacks and fuel processors. A demonstration project has been planned in existing residential homes to evaluate the proposal. The demonstration will be presented in a small apartment building. The building will be renovated and will be equipped with a hydrogen production facility, a hydrogen interchange pipe, and fuel cell stacks with a heat recovery device. The energy flow process from hydrogen production to consumption in the homes will be demonstrated. This paper presents the proposed energy interchange system and demonstration project. (authors)

  7. Antenna analysis using neural networks

    Science.gov (United States)

    Smith, William T.

    1992-01-01

    Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern

  8. Data Analysis for ARRA Early Fuel Cell Market Demonstrations (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Kurtz, J.; Wipke, K.; Sprik, S.; Ramsden, T.

    2010-05-01

    Presentation about ARRA Early Fuel Cell Market Demonstrations, including an overview of the ARRE Fuel Cell Project, the National Renewable Energy Laboratory's data analysis objectives, deployment composite data products, and planned analyses.

  9. Experimental demonstration of software defined data center optical networks with Tbps end-to-end tunability

    Science.gov (United States)

    Zhao, Yongli; Zhang, Jie; Ji, Yuefeng; Li, Hui; Wang, Huitao; Ge, Chao

    2015-10-01

    The end-to-end tunability is important to provision elastic channel for the burst traffic of data center optical networks. Then, how to complete the end-to-end tunability based on elastic optical networks? Software defined networking (SDN) based end-to-end tunability solution is proposed for software defined data center optical networks, and the protocol extension and implementation procedure are designed accordingly. For the first time, the flexible grid all optical networks with Tbps end-to-end tunable transport and switch system have been online demonstrated for data center interconnection, which are controlled by OpenDayLight (ODL) based controller. The performance of the end-to-end tunable transport and switch system has been evaluated with wavelength number tuning, bit rate tuning, and transmit power tuning procedure.

  10. Albemarle Sound demonstration study of the national monitoring network for US coastal waters and their tributaries

    Science.gov (United States)

    Michelle Moorman; Sharon Fitzgerald; Keith Loftin; Elizabeth Fensin

    2016-01-01

    The U.S. Geological Survey’s (USGS) is implementing a demonstration project in the Albemarle Sound for the National Monitoring Network for U.S. coastal waters and their tributaries. The goal of the National Monitoring Network is to provide information about the health of our oceans and coastal ecosystems and inland influences on coastal waters for improved resource...

  11. NET-2 Network Analysis Program

    International Nuclear Information System (INIS)

    Malmberg, A.F.

    1974-01-01

    The NET-2 Network Analysis Program is a general purpose digital computer program which solves the nonlinear time domain response and the linearized small signal frequency domain response of an arbitrary network of interconnected components. NET-2 is capable of handling a variety of components and has been applied to problems in several engineering fields, including electronic circuit design and analysis, missile flight simulation, control systems, heat flow, fluid flow, mechanical systems, structural dynamics, digital logic, communications network design, solid state device physics, fluidic systems, and nuclear vulnerability due to blast, thermal, gamma radiation, neutron damage, and EMP effects. Network components may be selected from a repertoire of built-in models or they may be constructed by the user through appropriate combinations of mathematical, empirical, and topological functions. Higher-level components may be defined by subnetworks composed of any combination of user-defined components and built-in models. The program provides a modeling capability to represent and intermix system components on many levels, e.g., from hole and electron spatial charge distributions in solid state devices through discrete and integrated electronic components to functional system blocks. NET-2 is capable of simultaneous computation in both the time and frequency domain, and has statistical and optimization capability. Network topology may be controlled as a function of the network solution. (U.S.)

  12. Integrating neural network technology and noise analysis

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Oak Ridge National Lab., TN

    1995-01-01

    The integrated use of neural network and noise analysis technologies offers advantages not available by the use of either technology alone. The application of neural network technology to noise analysis offers an opportunity to expand the scope of problems where noise analysis is useful and unique ways in which the integration of these technologies can be used productively. The two-sensor technique, in which the responses of two sensors to an unknown driving source are related, is used to demonstration such integration. The relationship between power spectral densities (PSDs) of accelerometer signals is derived theoretically using noise analysis to demonstrate its uniqueness. This relationship is modeled from experimental data using a neural network when the system is working properly, and the actual PSD of one sensor is compared with the PSD of that sensor predicted by the neural network using the PSD of the other sensor as an input. A significant deviation between the actual and predicted PSDs indicate that system is changing (i.e., failing). Experiments carried out on check values and bearings illustrate the usefulness of the methodology developed. (Author)

  13. Network Analysis Tools: from biological networks to clusters and pathways.

    Science.gov (United States)

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

    2008-01-01

    Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

  14. Statistical network analysis for analyzing policy networks

    DEFF Research Database (Denmark)

    Robins, Garry; Lewis, Jenny; Wang, Peng

    2012-01-01

    and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs......To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social......), and stochastic actor-oriented models. We focus most attention on ERGMs by providing an illustrative example of a model for a strategic information network within a local government. We draw inferences about the structural role played by individuals recognized as key innovators and conclude that such an approach...

  15. Statistical analysis of network data with R

    CERN Document Server

    Kolaczyk, Eric D

    2014-01-01

    Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

  16. Trimming of mammalian transcriptional networks using network component analysis

    Directory of Open Access Journals (Sweden)

    Liao James C

    2010-10-01

    Full Text Available Abstract Background Network Component Analysis (NCA has been used to deduce the activities of transcription factors (TFs from gene expression data and the TF-gene binding relationship. However, the TF-gene interaction varies in different environmental conditions and tissues, but such information is rarely available and cannot be predicted simply by motif analysis. Thus, it is beneficial to identify key TF-gene interactions under the experimental condition based on transcriptome data. Such information would be useful in identifying key regulatory pathways and gene markers of TFs in further studies. Results We developed an algorithm to trim network connectivity such that the important regulatory interactions between the TFs and the genes were retained and the regulatory signals were deduced. Theoretical studies demonstrated that the regulatory signals were accurately reconstructed even in the case where only three independent transcriptome datasets were available. At least 80% of the main target genes were correctly predicted in the extreme condition of high noise level and small number of datasets. Our algorithm was tested with transcriptome data taken from mice under rapamycin treatment. The initial network topology from the literature contains 70 TFs, 778 genes, and 1423 edges between the TFs and genes. Our method retained 1074 edges (i.e. 75% of the original edge number and identified 17 TFs as being significantly perturbed under the experimental condition. Twelve of these TFs are involved in MAPK signaling or myeloid leukemia pathways defined in the KEGG database, or are known to physically interact with each other. Additionally, four of these TFs, which are Hif1a, Cebpb, Nfkb1, and Atf1, are known targets of rapamycin. Furthermore, the trimmed network was able to predict Eno1 as an important target of Hif1a; this key interaction could not be detected without trimming the regulatory network. Conclusions The advantage of our new algorithm

  17. AEP Ohio gridSMART Demonstration Project Real-Time Pricing Demonstration Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Widergren, Steven E.; Subbarao, Krishnappa; Fuller, Jason C.; Chassin, David P.; Somani, Abhishek; Marinovici, Maria C.; Hammerstrom, Janelle L.

    2014-02-01

    This report contributes initial findings from an analysis of significant aspects of the gridSMART® Real-Time Pricing (RTP) – Double Auction demonstration project. Over the course of four years, Pacific Northwest National Laboratory (PNNL) worked with American Electric Power (AEP), Ohio and Battelle Memorial Institute to design, build, and operate an innovative system to engage residential consumers and their end-use resources in a participatory approach to electric system operations, an incentive-based approach that has the promise of providing greater efficiency under normal operating conditions and greater flexibility to react under situations of system stress. The material contained in this report supplements the findings documented by AEP Ohio in the main body of the gridSMART report. It delves into three main areas: impacts on system operations, impacts on households, and observations about the sensitivity of load to price changes.

  18. Mathematical Analysis of Urban Spatial Networks

    CERN Document Server

    Blanchard, Philippe

    2009-01-01

    Cities can be considered to be among the largest and most complex artificial networks created by human beings. Due to the numerous and diverse human-driven activities, urban network topology and dynamics can differ quite substantially from that of natural networks and so call for an alternative method of analysis. The intent of the present monograph is to lay down the theoretical foundations for studying the topology of compact urban patterns, using methods from spectral graph theory and statistical physics. These methods are demonstrated as tools to investigate the structure of a number of real cities with widely differing properties: medieval German cities, the webs of city canals in Amsterdam and Venice, and a modern urban structure such as found in Manhattan. Last but not least, the book concludes by providing a brief overview of possible applications that will eventually lead to a useful body of knowledge for architects, urban planners and civil engineers.

  19. Experimental demonstration of spectrum-sliced elastic optical path network (SLICE).

    Science.gov (United States)

    Kozicki, Bartłomiej; Takara, Hidehiko; Tsukishima, Yukio; Yoshimatsu, Toshihide; Yonenaga, Kazushige; Jinno, Masahiko

    2010-10-11

    We describe experimental demonstration of spectrum-sliced elastic optical path network (SLICE) architecture. We employ optical orthogonal frequency-division multiplexing (OFDM) modulation format and bandwidth-variable optical cross-connects (OXC) to generate, transmit and receive optical paths with bandwidths of up to 1 Tb/s. We experimentally demonstrate elastic optical path setup and spectrally-efficient transmission of multiple channels with bit rates ranging from 40 to 140 Gb/s between six nodes of a mesh network. We show dynamic bandwidth scalability for optical paths with bit rates of 40 to 440 Gb/s. Moreover, we demonstrate multihop transmission of a 1 Tb/s optical path over 400 km of standard single-mode fiber (SMF). Finally, we investigate the filtering properties and the required guard band width for spectrally-efficient allocation of optical paths in SLICE.

  20. Analysis techniques for background rejection at the Majorana Demonstrator

    Energy Technology Data Exchange (ETDEWEB)

    Cuestra, Clara [University of Washington; Rielage, Keith Robert [Los Alamos National Laboratory; Elliott, Steven Ray [Los Alamos National Laboratory; Xu, Wenqin [Los Alamos National Laboratory; Goett, John Jerome III [Los Alamos National Laboratory

    2015-06-11

    The MAJORANA Collaboration is constructing the MAJORANA DEMONSTRATOR, an ultra-low background, 40-kg modular HPGe detector array to search for neutrinoless double beta decay in 76Ge. In view of the next generation of tonne-scale Ge-based 0νββ-decay searches that will probe the neutrino mass scale in the inverted-hierarchy region, a major goal of the MAJORANA DEMONSTRATOR is to demonstrate a path forward to achieving a background rate at or below 1 count/tonne/year in the 4 keV region of interest around the Q-value at 2039 keV. The background rejection techniques to be applied to the data include cuts based on data reduction, pulse shape analysis, event coincidences, and time correlations. The Point Contact design of the DEMONSTRATOR's germanium detectors allows for significant reduction of gamma background.

  1. Analysis of Skylab IV fluid mechanic science demonstration

    Science.gov (United States)

    Klett, M. G.; Bourgeois, S. V.

    1975-01-01

    Several science demonstrations performed on Skylab III and IV were concerned with the behavior of fluid drops free floating in microgravity. These demonstrations, with large liquid drops, included the oscillation, rotation, impact and coalescence, and air injection into the drops. Rayleigh's analysis of the oscillation of spherical drops of a liquid predicts accurately the effect of size and surface tension on the frequency of vibrated water globules in the Skylab demonstration. However, damping occurred much faster than predicted by Lamb's or Scriven's analyses of the damping time for spherical drops. The impact demonstrations indicated that a minimum velocity is necessary to overcome surface forces and effect a coalescence, but a precise criterion for the coalescence of liquids in low g could not be determined.

  2. Analysis of Semantic Networks using Complex Networks Concepts

    DEFF Research Database (Denmark)

    Ortiz-Arroyo, Daniel

    2013-01-01

    In this paper we perform a preliminary analysis of semantic networks to determine the most important terms that could be used to optimize a summarization task. In our experiments, we measure how the properties of a semantic network change, when the terms in the network are removed. Our preliminar...

  3. Spectral Analysis of Rich Network Topology in Social Networks

    Science.gov (United States)

    Wu, Leting

    2013-01-01

    Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

  4. Experimental demonstration of optical stealth transmission over wavelength-division multiplexing network.

    Science.gov (United States)

    Zhu, Huatao; Wang, Rong; Pu, Tao; Fang, Tao; Xiang, Peng; Zheng, Jilin; Tang, Yeteng; Chen, Dalei

    2016-08-10

    We propose and experimentally demonstrate an optical stealth transmission system over a 200 GHz-grid wavelength-division multiplexing (WDM) network. The stealth signal is processed by spectral broadening, temporal spreading, and power equalizing. The public signal is suppressed by multiband notch filtering at the stealth channel receiver. The interaction between the public and stealth channels is investigated in terms of public-signal-to-stealth-signal ratio, data rate, notch-filter bandwidth, and public channel number. The stealth signal can transmit over 80 km single-mode fiber with no error. Our experimental results verify the feasibility of optical steganography used over the existing WDM-based optical network.

  5. Complex Network Analysis of Guangzhou Metro

    OpenAIRE

    Yasir Tariq Mohmand; Fahad Mehmood; Fahd Amjad; Nedim Makarevic

    2015-01-01

    The structure and properties of public transportation networks can provide suggestions for urban planning and public policies. This study contributes a complex network analysis of the Guangzhou metro. The metro network has 236 kilometers of track and is the 6th busiest metro system of the world. In this paper topological properties of the network are explored. We observed that the network displays small world properties and is assortative in nature. The network possesses a high average degree...

  6. COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks

    NARCIS (Netherlands)

    Sie, Rory

    2012-01-01

    Sie, R. L. L. (2012). COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks (Unpublished doctoral dissertation). September, 28, 2012, Open Universiteit in the Netherlands (CELSTEC), Heerlen, The Netherlands.

  7. Delay/Disruption Tolerant Networks (DTN): Testing and Demonstration for Lunar Surface Applications

    Science.gov (United States)

    2009-01-01

    This slide presentation reviews the testing of the Delay/Disruption Tolerant Network (DTN) designed for use with Lunar Surface applications. This is being done through the DTN experimental Network (DEN), that permit access and testing by other NASA centers, DTN team members and protocol developers. The objective of this work is to demonstrate DTN for high return applications in lunar scenarios, provide DEN connectivity with analogs of Constellation elements, emulators, and other resources from DTN Team Members, serve as a wireless communications staging ground for remote analog excursions and enable testing of detailed communication scenarios and evaluation of network performance. Three scenarios for DTN on the Lunar surface are reviewed: Motion imagery, Voice and sensor telemetry, and Navigation telemetry.

  8. Modelling and Simulation of National Electronic Product Code Network Demonstrator Project

    Science.gov (United States)

    Mo, John P. T.

    The National Electronic Product Code (EPC) Network Demonstrator Project (NDP) was the first large scale consumer goods track and trace investigation in the world using full EPC protocol system for applying RFID technology in supply chains. The NDP demonstrated the methods of sharing information securely using EPC Network, providing authentication to interacting parties, and enhancing the ability to track and trace movement of goods within the entire supply chain involving transactions among multiple enterprise. Due to project constraints, the actual run of the NDP was 3 months only and was unable to consolidate with quantitative results. This paper discusses the modelling and simulation of activities in the NDP in a discrete event simulation environment and provides an estimation of the potential benefits that can be derived from the NDP if it was continued for one whole year.

  9. Demonstration of hybrid orbital angular momentum multiplexing and time-division multiplexing passive optical network.

    Science.gov (United States)

    Wang, Andong; Zhu, Long; Liu, Jun; Du, Cheng; Mo, Qi; Wang, Jian

    2015-11-16

    Mode-division multiplexing passive optical network (MDM-PON) is a promising scheme for next-generation access networks to further increase fiber transmission capacity. In this paper, we demonstrate the proof-of-concept experiment of hybrid mode-division multiplexing (MDM) and time-division multiplexing (TDM) PON architecture by exploiting orbital angular momentum (OAM) modes. Bidirectional transmissions with 2.5-Gbaud 4-level pulse amplitude modulation (PAM-4) downstream and 2-Gbaud on-off keying (OOK) upstream are demonstrated in the experiment. The observed optical signal-to-noise ratio (OSNR) penalties for downstream and upstream transmissions at a bit-error rate (BER) of 2 × 10(-3) are less than 2.0 dB and 3.0 dB, respectively.

  10. Performance demonstration program plan for analysis of simulated headspace gases

    International Nuclear Information System (INIS)

    1995-06-01

    The Performance Demonstration Program (PDP) for analysis of headspace gases will consist of regular distribution and analyses of test standards to evaluate the capability for analyzing VOCs, hydrogen, and methane in the headspace of transuranic (TRU) waste throughout the Department of Energy (DOE) complex. Each distribution is termed a PDP cycle. These evaluation cycles will provide an objective measure of the reliability of measurements performed for TRU waste characterization. Laboratory performance will be demonstrated by the successful analysis of blind audit samples of simulated TRU waste drum headspace gases according to the criteria set within the text of this Program Plan. Blind audit samples (hereinafter referred to as PDP samples) will be used as an independent means to assess laboratory performance regarding compliance with the QAPP QAOs. The concentration of analytes in the PDP samples will encompass the range of concentrations anticipated in actual waste characterization gas samples. Analyses which are required by the WIPP to demonstrate compliance with various regulatory requirements and which are included in the PDP must be performed by laboratories which have demonstrated acceptable performance in the PDP

  11. Networks and network analysis for defence and security

    CERN Document Server

    Masys, Anthony J

    2014-01-01

    Networks and Network Analysis for Defence and Security discusses relevant theoretical frameworks and applications of network analysis in support of the defence and security domains. This book details real world applications of network analysis to support defence and security. Shocks to regional, national and global systems stemming from natural hazards, acts of armed violence, terrorism and serious and organized crime have significant defence and security implications. Today, nations face an uncertain and complex security landscape in which threats impact/target the physical, social, economic

  12. Vulnerability analysis methods for road networks

    Science.gov (United States)

    Bíl, Michal; Vodák, Rostislav; Kubeček, Jan; Rebok, Tomáš; Svoboda, Tomáš

    2014-05-01

    Road networks rank among the most important lifelines of modern society. They can be damaged by either random or intentional events. Roads are also often affected by natural hazards, the impacts of which are both direct and indirect. Whereas direct impacts (e.g. roads damaged by a landslide or due to flooding) are localized in close proximity to the natural hazard occurrence, the indirect impacts can entail widespread service disabilities and considerable travel delays. The change in flows in the network may affect the population living far from the places originally impacted by the natural disaster. These effects are primarily possible due to the intrinsic nature of this system. The consequences and extent of the indirect costs also depend on the set of road links which were damaged, because the road links differ in terms of their importance. The more robust (interconnected) the road network is, the less time is usually needed to secure the serviceability of an area hit by a disaster. These kinds of networks also demonstrate a higher degree of resilience. Evaluating road network structures is therefore essential in any type of vulnerability and resilience analysis. There are a range of approaches used for evaluation of the vulnerability of a network and for identification of the weakest road links. Only few of them are, however, capable of simulating the impacts of the simultaneous closure of numerous links, which often occurs during a disaster. The primary problem is that in the case of a disaster, which usually has a large regional extent, the road network may remain disconnected. The majority of the commonly used indices use direct computation of the shortest paths or time between OD (origin - destination) pairs and therefore cannot be applied when the network breaks up into two or more components. Since extensive break-ups often occur in cases of major disasters, it is important to study the network vulnerability in these cases as well, so that appropriate

  13. Beyond ectomycorrhizal bipartite networks: projected networks demonstrate contrasted patterns between early- and late-successional plants in Corsica.

    Directory of Open Access Journals (Sweden)

    Adrien eTaudiere

    2015-10-01

    Full Text Available The ectomycorrhizal (ECM symbiosis connects mutualistic plants and fungal species into bipartite networks. While links between one focal ECM plant and its fungal symbionts have been widely documented, systemic views of ECM networks are lacking, in particular, concerning the ability of fungal species to mediate indirect ecological interactions between ECM plant species (projected-ECM networks. We assembled a large dataset of plant-fungi associations at the species level and at the scale of Corsica using molecular data and unambiguously host-assigned records to: (i examine the correlation between the number of fungal symbionts of a plant species and the average specialization of these fungal species, (ii explore the structure of the plant-plant projected network and (iii compare plant association patterns in regard to their position along the ecological succession. Our analysis reveals no trade-off between specialization of plants and specialization of their partners and a saturation of the plant projected network. Moreover, there is a significantly lower-than-expected sharing of partners between early- and late-successional plant species, with fewer fungal partners for early-successional ones and similar average specialization of symbionts of early- and late-successional plants. Our work paves the way for ecological readings of Mediterranean landscapes that include the astonishing diversity of below-ground interactions.

  14. Experimental demonstration of large capacity WSDM optical access network with multicore fibers and advanced modulation formats.

    Science.gov (United States)

    Li, Borui; Feng, Zhenhua; Tang, Ming; Xu, Zhilin; Fu, Songnian; Wu, Qiong; Deng, Lei; Tong, Weijun; Liu, Shuang; Shum, Perry Ping

    2015-05-04

    Towards the next generation optical access network supporting large capacity data transmission to enormous number of users covering a wider area, we proposed a hybrid wavelength-space division multiplexing (WSDM) optical access network architecture utilizing multicore fibers with advanced modulation formats. As a proof of concept, we experimentally demonstrated a WSDM optical access network with duplex transmission using our developed and fabricated multicore (7-core) fibers with 58.7km distance. As a cost-effective modulation scheme for access network, the optical OFDM-QPSK signal has been intensity modulated on the downstream transmission in the optical line terminal (OLT) and it was directly detected in the optical network unit (ONU) after MCF transmission. 10 wavelengths with 25GHz channel spacing from an optical comb generator are employed and each wavelength is loaded with 5Gb/s OFDM-QPSK signal. After amplification, power splitting, and fan-in multiplexer, 10-wavelength downstream signal was injected into six outer layer cores simultaneously and the aggregation downstream capacity reaches 300 Gb/s. -16 dBm sensitivity has been achieved for 3.8 × 10-3 bit error ratio (BER) with 7% Forward Error Correction (FEC) limit for all wavelengths in every core. Upstream signal from ONU side has also been generated and the bidirectional transmission in the same core causes negligible performance degradation to the downstream signal. As a universal platform for wired/wireless data access, our proposed architecture provides additional dimension for high speed mobile signal transmission and we hence demonstrated an upstream delivery of 20Gb/s per wavelength with QPSK modulation formats using the inner core of MCF emulating a mobile backhaul service. The IQ modulated data was coherently detected in the OLT side. -19 dBm sensitivity has been achieved under the FEC limit and more than 18 dB power budget is guaranteed.

  15. Post mitigation impact risk analysis for asteroid deflection demonstration missions

    Science.gov (United States)

    Eggl, Siegfried; Hestroffer, Daniel; Thuillot, William; Bancelin, David; Cano, Juan L.; Cichocki, Filippo

    2015-08-01

    Even though mankind believes to have the capabilities to avert potentially disastrous asteroid impacts, only the realization of mitigation demonstration missions can validate this claim. Such a deflection demonstration attempt has to be cost effective, easy to validate, and safe in the sense that harmless asteroids must not be turned into potentially hazardous objects. Uncertainties in an asteroid's orbital and physical parameters as well as those additionally introduced during a mitigation attempt necessitate an in depth analysis of deflection mission designs in order to dispel planetary safety concerns. We present a post mitigation impact risk analysis of a list of potential kinetic impactor based deflection demonstration missions proposed in the framework of the NEOShield project. Our results confirm that mitigation induced uncertainties have a significant influence on the deflection outcome. Those cannot be neglected in post deflection impact risk studies. We show, furthermore, that deflection missions have to be assessed on an individual basis in order to ensure that asteroids are not inadvertently transported closer to the Earth at a later date. Finally, we present viable targets and mission designs for a kinetic impactor test to be launched between the years 2025 and 2032.

  16. Performance Demonstration Program Plan for Analysis of Simulated Headspace Gases

    International Nuclear Information System (INIS)

    2006-01-01

    The Performance Demonstration Program (PDP) for headspace gases distributes sample gases of volatile organic compounds (VOCs) for analysis. Participating measurement facilities (i.e., fixed laboratories, mobile analysis systems, and on-line analytical systems) are located across the United States. Each sample distribution is termed a PDP cycle. These evaluation cycles provide an objective measure of the reliability of measurements performed for transuranic (TRU) waste characterization. The primary documents governing the conduct of the PDP are the Quality Assurance Program Document (QAPD) (DOE/CBFO-94-1012) and the Waste Isolation Pilot Plant (WIPP) Waste Analysis Plan (WAP) contained in the Hazardous Waste Facility Permit (NM4890139088-TSDF) issued by the New Mexico Environment Department (NMED). The WAP requires participation in the PDP; the PDP must comply with the QAPD and the WAP. This plan implements the general requirements of the QAPD and the applicable requirements of the WAP for the Headspace Gas (HSG) PDP. Participating measurement facilities analyze blind audit samples of simulated TRU waste package headspace gases according to the criteria set by this PDP Plan. Blind audit samples (hereafter referred to as PDP samples) are used as an independent means to assess each measurement facility's compliance with the WAP quality assurance objectives (QAOs). To the extent possible, the concentrations of VOC analytes in the PDP samples encompass the range of concentrations anticipated in actual TRU waste package headspace gas samples. Analyses of headspace gases are required by the WIPP to demonstrate compliance with regulatory requirements. These analyses must be performed by measurement facilities that have demonstrated acceptable performance in this PDP. These analyses are referred to as WIPP analyses and the TRU waste package headspace gas samples on which they are performed are referred to as WIPP samples in this document. Participating measurement

  17. Performance Demonstration Program Plan for Analysis of Simulated Headspace Gases

    International Nuclear Information System (INIS)

    2007-01-01

    The Performance Demonstration Program (PDP) for headspace gases distributes blind audit samples in a gas matrix for analysis of volatile organic compounds (VOCs). Participating measurement facilities (i.e., fixed laboratories, mobile analysis systems, and on-line analytical systems) are located across the United States. Each sample distribution is termed a PDP cycle. These evaluation cycles provide an objective measure of the reliability of measurements performed for transuranic (TRU) waste characterization. The primary documents governing the conduct of the PDP are the Quality Assurance Program Document (QAPD) (DOE/CBFO-94-1012) and the Waste Isolation Pilot Plant (WIPP) Waste Analysis Plan (WAP) contained in the Hazardous Waste Facility Permit (NM4890139088-TSDF) issued by the New Mexico Environment Department (NMED). The WAP requires participation in the PDP; the PDP must comply with the QAPD and the WAP. This plan implements the general requirements of the QAPD and the applicable requirements of the WAP for the Headspace Gas (HSG) PDP. Participating measurement facilities analyze blind audit samples of simulated TRU waste package headspace gases according to the criteria set by this PDP Plan. Blind audit samples (hereafter referred to as PDP samples) are used as an independent means to assess each measurement facility's compliance with the WAP quality assurance objectives (QAOs). To the extent possible, the concentrations of VOC analytes in the PDP samples encompass the range of concentrations anticipated in actual TRU waste package headspace gas samples. Analyses of headspace gases are required by the WIPP to demonstrate compliance with regulatory requirements. These analyses must be performed by measurement facilities that have demonstrated acceptable performance in this PDP. These analyses are referred to as WIPP analyses and the TRU waste package headspace gas samples on which they are performed are referred to as WIPP samples in this document

  18. Social Network Analysis and informal trade

    DEFF Research Database (Denmark)

    Walther, Olivier

    networks can be applied to better understand informal trade in developing countries, with a particular focus on Africa. The paper starts by discussing some of the fundamental concepts developed by social network analysis. Through a number of case studies, we show how social network analysis can...... illuminate the relevant causes of social patterns, the impact of social ties on economic performance, the diffusion of resources and information, and the exercise of power. The paper then examines some of the methodological challenges of social network analysis and how it can be combined with other...... approaches. The paper finally highlights some of the applications of social network analysis and their implications for trade policies....

  19. Experimental demonstration of topologically protected efficient sound propagation in an acoustic waveguide network

    Science.gov (United States)

    Wei, Qi; Tian, Ye; Zuo, Shu-Yu; Cheng, Ying; Liu, Xiao-Jun

    2017-03-01

    Acoustic topological states support sound propagation along the boundary in a one-way direction with inherent robustness against defects and disorders, leading to the revolution of the manipulation on acoustic waves. A variety of acoustic topological states relying on circulating fluid, chiral coupling, or temporal modulation have been proposed theoretically. However, experimental demonstration has so far remained a significant challenge, due to the critical limitations such as structural complexity and high losses. Here, we experimentally demonstrate an acoustic anomalous Floquet topological insulator in a waveguide network. The acoustic gapless edge states can be found in the band gap when the waveguides are strongly coupled. The scheme features simple structure and high-energy throughput, leading to the experimental demonstration of efficient and robust topologically protected sound propagation along the boundary. The proposal may offer a unique, promising application for design of acoustic devices in acoustic guiding, switching, isolating, filtering, etc.

  20. CATHENA 4. A thermalhydraulics network analysis code

    International Nuclear Information System (INIS)

    Aydemir, N.U.; Hanna, B.N.

    2009-01-01

    Canadian Algorithm for THErmalhydraulic Network Analysis (CATHENA) is a one-dimensional, non-equilibrium, two-phase, two fluid network analysis code that has been in use for over two decades by various groups in Canada and around the world. The objective of the present paper is to describe the design, application and future development plans for the CATHENA 4 thermalhydraulics network analysis code, which is a modernized version of the present frozen CATHENA 3 code. The new code is designed in modular form, using the Fortran 95 (F95) programming language. The semi-implicit numerical integration scheme of CATHENA 3 is re-written to implement a fully-implicit methodology using Newton's iterative solution scheme suitable for nonlinear equations. The closure relations, as a first step, have been converted from the existing CATHENA 3 implementation to F95 but modularized to achieve ease of maintenance. The paper presents the field equations, followed by a description of the Newton's scheme used. The finite-difference form of the field equations is given, followed by a discussion of convergence criteria. Two applications of CATHENA 4 are presented to demonstrate the temporal and spatial convergence of the new code for problems with known solutions or available experimental data. (author)

  1. Analysis of Network Parameters Influencing Performance of Hybrid Multimedia Networks

    Directory of Open Access Journals (Sweden)

    Dominik Kovac

    2013-10-01

    Full Text Available Multimedia networks is an emerging subject that currently attracts the attention of research and industrial communities. This environment provides new entertainment services and business opportunities merged with all well-known network services like VoIP calls or file transfers. Such a heterogeneous system has to be able satisfy all network and end-user requirements which are increasing constantly. Therefore the simulation tools enabling deep analysis in order to find the key performance indicators and factors which influence the overall quality for specific network service the most are highly needed. This paper provides a study on the network parameters like communication technology, routing protocol, QoS mechanism, etc. and their effect on the performance of hybrid multimedia network. The analysis was performed in OPNET Modeler environment and the most interesting results are discussed at the end of this paper

  2. Experimental demonstration of time- and mode-division multiplexed passive optical network

    Science.gov (United States)

    Ren, Fang; Li, Juhao; Tang, Ruizhi; Hu, Tao; Yu, Jinyi; Mo, Qi; He, Yongqi; Chen, Zhangyuan; Li, Zhengbin

    2017-07-01

    A time- and mode-division multiplexed passive optical network (TMDM-PON) architecture is proposed, in which each optical network unit (ONU) communicates with the optical line terminal (OLT) independently utilizing both different time slots and switched optical linearly polarized (LP) spatial modes. Combination of a mode multiplexer/demultiplexer (MUX/DEUX) and a simple N × 1 optical switch is employed to select the specific LP mode in each ONU. A mode-insensitive power splitter is used for signal broadcast/combination between OLT and ONUs. We theoretically propose a dynamic mode and time slot assignment scheme for TMDM-PON based on inter-ONU priority rating, in which the time delay and packet loss ratio's variation tendency are investigated by simulation. Moreover, we experimentally demonstrate 2-mode TMDM-PON transmission over 10 km FMF with 10-Gb/s on-off keying (OOK) signal and direct detection.

  3. Functional Module Analysis for Gene Coexpression Networks with Network Integration.

    Science.gov (United States)

    Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

  4. Capacity Analysis of Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    M. I. Gumel

    2012-06-01

    Full Text Available The next generation wireless networks experienced a great development with emergence of wireless mesh networks (WMNs, which can be regarded as a realistic solution that provides wireless broadband access. The limited available bandwidth makes capacity analysis of the network very essential. While the network offers broadband wireless access to community and enterprise users, the problems that limit the network capacity must be addressed to exploit the optimum network performance. The wireless mesh network capacity analysis shows that the throughput of each mesh node degrades in order of l/n with increasing number of nodes (n in a linear topology. The degradation is found to be higher in a fully mesh network as a result of increase in interference and MAC layer contention in the network.

  5. Social network analysis community detection and evolution

    CERN Document Server

    Missaoui, Rokia

    2015-01-01

    This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edit

  6. SOCIOLOGICAL UNDERSTANDING OF INTERNET: THEORETICAL APPROACHES TO THE NETWORK ANALYSIS

    Directory of Open Access Journals (Sweden)

    D. E. Dobrinskaya

    2016-01-01

    Full Text Available The network is an efficient way of social structure analysis for contemporary sociologists. It gives broad opportunities for detailed and fruitful research of different patterns of ties and social relations by quantitative analytical methods and visualization of network models. The network metaphor is used as the most representative tool for description of a new type of society. This new type is characterized by flexibility, decentralization and individualization. Network organizational form became the dominant form in modern societies. The network is also used as a mode of inquiry. Actually three theoretical network approaches in the Internet research case are the most relevant: social network analysis, “network society” theory and actor-network theory. Every theoretical approach has got its own notion of network. Their special methodological and theoretical features contribute to the Internet studies in different ways. The article represents a brief overview of these network approaches. This overview demonstrates the absence of a unified semantic space of the notion of “network” category. This fact, in turn, points out the need for detailed analysis of these approaches to reveal their theoretical and empirical possibilities in application to the Internet studies. 

  7. Network analysis literacy a practical approach to the analysis of networks

    CERN Document Server

    Zweig, Katharina A

    2014-01-01

    Network Analysis Literacy focuses on design principles for network analytics projects. The text enables readers to: pose a defined network analytic question; build a network to answer the question; choose or design the right network analytic methods for a particular purpose, and more.

  8. Statistical Network Analysis for Functional MRI: Mean Networks and Group Comparisons.

    Directory of Open Access Journals (Sweden)

    Cedric E Ginestet

    2014-05-01

    Full Text Available Comparing networks in neuroscience is hard, because the topological properties of a given network are necessarily dependent on the number of edges of that network. This problem arises in the analysis of both weighted and unweighted networks. The term density is often used in this context, in order to refer to the mean edge weight of a weighted network, or to the number of edges in an unweighted one. Comparing families of networks is therefore statistically difficult because differences in topology are necessarily associated with differences in density. In this review paper, we consider this problem from two different perspectives, which include (i the construction of summary networks, such as how to compute and visualize the mean network from a sample of network-valued data points; and (ii how to test for topological differences, when two families of networks also exhibit significant differences in density. In the first instance, we show that the issue of summarizing a family of networks can be conducted by either adopting a mass-univariate approach, which produces a statistical parametric network (SPN, or by directly computing the mean network, provided that a metric has been specified on the space of all networks with a given number of nodes. In the second part of this review, we then highlight the inherent problems associated with the comparison of topological functions of families of networks that differ in density. In particular, we show that a wide range of topological summaries, such as global efficiency and network modularity are highly sensitive to differences in density. Moreover, these problems are not restricted to unweighted metrics, as we demonstrate that the same issues remain present when considering the weighted versions of these metrics. We conclude by encouraging caution, when reporting such statistical comparisons, and by emphasizing the importance of constructing summary networks.

  9. Networks and Bargaining in Policy Analysis

    DEFF Research Database (Denmark)

    Bogason, Peter

    2006-01-01

    A duscussion of the fight between proponents of rationalistic policy analysis and more political interaction models for policy analysis. The latter group is the foundation for the many network models of policy analysis of today.......A duscussion of the fight between proponents of rationalistic policy analysis and more political interaction models for policy analysis. The latter group is the foundation for the many network models of policy analysis of today....

  10. Analysis of Recurrent Analog Neural Networks

    Directory of Open Access Journals (Sweden)

    Z. Raida

    1998-06-01

    Full Text Available In this paper, an original rigorous analysis of recurrent analog neural networks, which are built from opamp neurons, is presented. The analysis, which comes from the approximate model of the operational amplifier, reveals causes of possible non-stable states and enables to determine convergence properties of the network. Results of the analysis are discussed in order to enable development of original robust and fast analog networks. In the analysis, the special attention is turned to the examination of the influence of real circuit elements and of the statistical parameters of processed signals to the parameters of the network.

  11. Research, development and demonstration. Issue paper - working group 3; Denmark. Smart Grid Network; Forskning, udvikling og demonstration. Issue paper, arbejdsgruppe 3

    Energy Technology Data Exchange (ETDEWEB)

    Balasiu, A [Siemens A/S, Ballerup (Denmark); Troi, A [Danmarks Tekniske Univ. Risoe Nationallaboratoriet for Baeredygtig Energi, Roskilde (Denmark); Andersen, Casper [DI Energibranchen, Copenhagen (Denmark); and others

    2011-07-01

    The Smart Grid Network was established in 2010 by the Danish climate and energy minister tasked with developing recommendations for future actions and initiatives that make it possible to handle up to 50% electricity from wind energy in the power system in 2020. The task of working group 3 was defined as: - An overview of the Danish research and development of smart grids and related areas; - Conducting an analysis of the research and development needs required for the introduction of a smart grid in Denmark. Based on this analysis, provide suggestions for new large research and development projects; - Provide recommendations on how the activities are best carried out taking into account innovation, economic growth and jobs. In the analysis it is explained that Denmark so far has a strong position in several elements of RD and D activities. This position will soon be threatened as several European countries have launched ambitious initiatives to strengthen the national position. The working group recommends that Denmark gives priority to Smart Grids as a national action in order to solve the challenge of technically and economically efficient integration of renewable energy. Smart Grid is a catalyst that strengthens a new green growth industry (cleantech) in Denmark. Research and development has an important role to play in this development. A common vision and roadmap must be established for research institutions, energy companies and industries related to research, development and demonstration of Smart Grid, which can maintain and expand Denmark's global leadership position. As part of this, there is a need to strengthen and market research infrastructures, which can turn Denmark into a global hub for smart grid development. There is a current need to strengthen the advanced technical and scientific research in the complexities of the power system, research on market design, user behavior and smart grid interoperability. (LN)

  12. Research, development and demonstration. Issue paper - working group 3; Denmark. Smart Grid Network; Forskning, udvikling og demonstration. Issue paper, arbejdsgruppe 3

    Energy Technology Data Exchange (ETDEWEB)

    Balasiu, A. (Siemens A/S, Ballerup (Denmark)); Troi, A. (Danmarks Tekniske Univ.. Risoe Nationallaboratoriet for Baeredygtig Energi, Roskilde (Denmark)); Andersen, Casper (DI Energibranchen, Copenhagen (Denmark)) (and others)

    2011-07-01

    The Smart Grid Network was established in 2010 by the Danish climate and energy minister tasked with developing recommendations for future actions and initiatives that make it possible to handle up to 50% electricity from wind energy in the power system in 2020. The task of working group 3 was defined as: - An overview of the Danish research and development of smart grids and related areas; - Conducting an analysis of the research and development needs required for the introduction of a smart grid in Denmark. Based on this analysis, provide suggestions for new large research and development projects; - Provide recommendations on how the activities are best carried out taking into account innovation, economic growth and jobs. In the analysis it is explained that Denmark so far has a strong position in several elements of RD and D activities. This position will soon be threatened as several European countries have launched ambitious initiatives to strengthen the national position. The working group recommends that Denmark gives priority to Smart Grids as a national action in order to solve the challenge of technically and economically efficient integration of renewable energy. Smart Grid is a catalyst that strengthens a new green growth industry (cleantech) in Denmark. Research and development has an important role to play in this development. A common vision and roadmap must be established for research institutions, energy companies and industries related to research, development and demonstration of Smart Grid, which can maintain and expand Denmark's global leadership position. As part of this, there is a need to strengthen and market research infrastructures, which can turn Denmark into a global hub for smart grid development. There is a current need to strengthen the advanced technical and scientific research in the complexities of the power system, research on market design, user behavior and smart grid interoperability. (LN)

  13. Egocentric Social Network Analysis of Pathological Gambling

    Science.gov (United States)

    Meisel, Matthew K.; Clifton, Allan D.; MacKillop, James; Miller, Joshua D.; Campbell, W. Keith; Goodie, Adam S.

    2012-01-01

    Aims To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family, and co-workers. is an innovative way to look at relationships among individuals; the current study was the first to our knowledge to apply SNA to gambling behaviors. Design Egocentric social network analysis was used to formally characterize the relationships between social network characteristics and gambling pathology. Setting Laboratory-based questionnaire and interview administration. Participants Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. Findings The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers, and drinkers in their social networks than did nonpathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked, and drank with than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked, and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Conclusions Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers, and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. PMID:23072641

  14. Egocentric social network analysis of pathological gambling.

    Science.gov (United States)

    Meisel, Matthew K; Clifton, Allan D; Mackillop, James; Miller, Joshua D; Campbell, W Keith; Goodie, Adam S

    2013-03-01

    To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family and co-workers is an innovative way to look at relationships among individuals; the current study was the first, to our knowledge, to apply SNA to gambling behaviors. Egocentric social network analysis was used to characterize formally the relationships between social network characteristics and gambling pathology. Laboratory-based questionnaire and interview administration. Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers and drinkers in their social networks than did non-pathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked and drank than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

  15. Photosynthesis energy factory: analysis, synthesis, and demonstration. Final report

    Energy Technology Data Exchange (ETDEWEB)

    1978-11-01

    This quantitative assessment of the potential of a combined dry-land Energy Plantation, wood-fired power plant, and algae wastewater treatment system demonstrates the cost-effectiveness of recycling certain by-products and effluents from one subsystem to another. Designed to produce algae up to the limit of the amount of carbon in municipal wastewater, the algae pond provides a positive cash credit, resulting mainly from the wastewater treatment credit, which may be used to reduce the cost of the Photosynthesis Energy Factory (PEF)-generated electricity. The algae pond also produces fertilizer, which reduces the cost of the biomass produced on the Energy Plantation, and some gas. The cost of electricity was as low as 35 mills per kilowatt-hour for a typical municipally-owned PEF consisting of a 65-MWe power plant, a 144-acre algae pond, and a 33,000-acre Energy Plantation. Using only conventional or near-term technology, the most cost-effective algae pond for a PEF is the carbon-limited secondary treatment system. This system does not recycle CO/sub 2/ from the flue gas. Analysis of the Energy Plantation subsystem at 15 sites revealed that plantations of 24,000 to 36,000 acres produce biomass at the lowest cost per ton. The following sites are recommended for more detailed evaluation as potential demonstration sites: Pensacola, Florida; Jamestown, New York; Knoxville, Tennessee; Martinsville, Virginia, and Greenwood, South Carolina. A major possible extension of the PEF concept is to include the possibility for irrigation.

  16. First demonstration of single-mode MCF transport network with crosstalk-aware in-service optical channel control

    DEFF Research Database (Denmark)

    Pulverer, K.; Tanaka, T.; Häbel, U.

    2017-01-01

    We demonstrate the first crosstalk-aware traffic engineering as a use case in a multicore fibre transport network. With the help of a software-defined network controller, modulation format and channel route are adaptively changed using programmable devices with XT monitors.......We demonstrate the first crosstalk-aware traffic engineering as a use case in a multicore fibre transport network. With the help of a software-defined network controller, modulation format and channel route are adaptively changed using programmable devices with XT monitors....

  17. Experimental demonstration of OpenFlow-enabled media ecosystem architecture for high-end applications over metro and core networks.

    Science.gov (United States)

    Ntofon, Okung-Dike; Channegowda, Mayur P; Efstathiou, Nikolaos; Rashidi Fard, Mehdi; Nejabati, Reza; Hunter, David K; Simeonidou, Dimitra

    2013-02-25

    In this paper, a novel Software-Defined Networking (SDN) architecture is proposed for high-end Ultra High Definition (UHD) media applications. UHD media applications require huge amounts of bandwidth that can only be met with high-capacity optical networks. In addition, there are requirements for control frameworks capable of delivering effective application performance with efficient network utilization. A novel SDN-based Controller that tightly integrates application-awareness with network control and management is proposed for such applications. An OpenFlow-enabled test-bed demonstrator is reported with performance evaluations of advanced online and offline media- and network-aware schedulers.

  18. Social network analysis and supply chain management

    Directory of Open Access Journals (Sweden)

    Raúl Rodríguez Rodríguez

    2016-01-01

    Full Text Available This paper deals with social network analysis and how it could be integrated within supply chain management from a decision-making point of view. Even though the benefits of using social analysis have are widely accepted at both academic and industry/services context, there is still a lack of solid frameworks that allow decision-makers to connect the usage and obtained results of social network analysis – mainly both information and knowledge flows and derived results- with supply chain management objectives and goals. This paper gives an overview of social network analysis, the main social network analysis metrics, supply chain performance and, finally, it identifies how future frameworks could close the gap and link the results of social network analysis with the supply chain management decision-making processes.

  19. G-computation demonstration in causal mediation analysis

    International Nuclear Information System (INIS)

    Wang, Aolin; Arah, Onyebuchi A.

    2015-01-01

    Recent work has considerably advanced the definition, identification and estimation of controlled direct, and natural direct and indirect effects in causal mediation analysis. Despite the various estimation methods and statistical routines being developed, a unified approach for effect estimation under different effect decomposition scenarios is still needed for epidemiologic research. G-computation offers such unification and has been used for total effect and joint controlled direct effect estimation settings, involving different types of exposure and outcome variables. In this study, we demonstrate the utility of parametric g-computation in estimating various components of the total effect, including (1) natural direct and indirect effects, (2) standard and stochastic controlled direct effects, and (3) reference and mediated interaction effects, using Monte Carlo simulations in standard statistical software. For each study subject, we estimated their nested potential outcomes corresponding to the (mediated) effects of an intervention on the exposure wherein the mediator was allowed to attain the value it would have under a possible counterfactual exposure intervention, under a pre-specified distribution of the mediator independent of any causes, or under a fixed controlled value. A final regression of the potential outcome on the exposure intervention variable was used to compute point estimates and bootstrap was used to obtain confidence intervals. Through contrasting different potential outcomes, this analytical framework provides an intuitive way of estimating effects under the recently introduced 3- and 4-way effect decomposition. This framework can be extended to complex multivariable and longitudinal mediation settings

  20. The Network Protocol Analysis Technique in Snort

    Science.gov (United States)

    Wu, Qing-Xiu

    Network protocol analysis is a network sniffer to capture data for further analysis and understanding of the technical means necessary packets. Network sniffing is intercepted by packet assembly binary format of the original message content. In order to obtain the information contained. Required based on TCP / IP protocol stack protocol specification. Again to restore the data packets at protocol format and content in each protocol layer. Actual data transferred, as well as the application tier.

  1. Ecological network analysis for a virtual water network.

    Science.gov (United States)

    Fang, Delin; Chen, Bin

    2015-06-02

    The notions of virtual water flows provide important indicators to manifest the water consumption and allocation between different sectors via product transactions. However, the configuration of virtual water network (VWN) still needs further investigation to identify the water interdependency among different sectors as well as the network efficiency and stability in a socio-economic system. Ecological network analysis is chosen as a useful tool to examine the structure and function of VWN and the interactions among its sectors. A balance analysis of efficiency and redundancy is also conducted to describe the robustness (RVWN) of VWN. Then, network control analysis and network utility analysis are performed to investigate the dominant sectors and pathways for virtual water circulation and the mutual relationships between pairwise sectors. A case study of the Heihe River Basin in China shows that the balance between efficiency and redundancy is situated on the left side of the robustness curve with less efficiency and higher redundancy. The forestation, herding and fishing sectors and industrial sectors are found to be the main controllers. The network tends to be more mutualistic and synergic, though some competitive relationships that weaken the virtual water circulation still exist.

  2. Basic general concepts in the network analysis

    Directory of Open Access Journals (Sweden)

    Boja Nicolae

    2004-01-01

    Full Text Available This survey is concerned oneself with the study of those types of material networks which can be met both in civil engineering and also in electrotechnics, in mechanics, or in hydrotechnics, and of which behavior lead to linear problems, solvable by means of Finite Element Method and adequate algorithms. Here, it is presented a unitary theory of networks met in the domains mentioned above and this one is illustrated with examples for the structural networks in civil engineering, electric circuits, and water supply networks, but also planar or spatial mechanisms can be comprised in this theory. The attention is focused to make evident the essential proper- ties and concepts in the network analysis, which differentiate the networks under force from other types of material networks. To such a network a planar, connected, and directed or undirected graph is associated, and with some vector fields on the vertex set this graph is endowed. .

  3. Network Analysis on Attitudes: A Brief Tutorial.

    Science.gov (United States)

    Dalege, Jonas; Borsboom, Denny; van Harreveld, Frenk; van der Maas, Han L J

    2017-07-01

    In this article, we provide a brief tutorial on the estimation, analysis, and simulation on attitude networks using the programming language R. We first discuss what a network is and subsequently show how one can estimate a regularized network on typical attitude data. For this, we use open-access data on the attitudes toward Barack Obama during the 2012 American presidential election. Second, we show how one can calculate standard network measures such as community structure, centrality, and connectivity on this estimated attitude network. Third, we show how one can simulate from an estimated attitude network to derive predictions from attitude networks. By this, we highlight that network theory provides a framework for both testing and developing formalized hypotheses on attitudes and related core social psychological constructs.

  4. 4th International Conference in Network Analysis

    CERN Document Server

    Koldanov, Petr; Pardalos, Panos

    2016-01-01

    The contributions in this volume cover a broad range of topics including maximum cliques, graph coloring, data mining, brain networks, Steiner forest, logistic and supply chain networks. Network algorithms and their applications to market graphs, manufacturing problems, internet networks and social networks are highlighted. The "Fourth International Conference in Network Analysis," held at the Higher School of Economics, Nizhny Novgorod in May 2014, initiated joint research between scientists, engineers and researchers from academia, industry and government; the major results of conference participants have been reviewed and collected in this Work. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis.

  5. Using Social Network Analysis to Investigate Positive EOL Communication.

    Science.gov (United States)

    Xu, Jiayun; Yang, Rumei; Wilson, Andrew; Reblin, Maija; Clayton, Margaret F; Ellington, Lee

    2018-04-30

    End of life (EOL) communication is a complex process involving the whole family and multiple care providers. Applications of analysis techniques that account for communication beyond the patient and patient/provider, will improve clinical understanding of EOL communication. To introduce the use of social network analysis to EOL communication data, and to provide an example of applying social network analysis to home hospice interactions. We provide a description of social network analysis using social network analysis to model communication patterns during home hospice nursing visits. We describe three social network attributes (i.e. magnitude, directionality, and reciprocity) in the expression of positive emotion among hospice nurses, family caregivers, and hospice cancer patients. Differences in communication structure by primary family caregiver gender and across time were also examined. Magnitude (frequency) in the expression of positive emotion occurred most often between nurses and caregivers or nurses and patients. Female caregivers directed more positive emotion to nurses, and nurses directed more positive emotion to other family caregivers when the primary family caregiver was male. Reciprocity (mutuality) in positive emotion declined towards day of death, but increased on day of actual patient death. There was variation in reciprocity by the type of positive emotion expressed. Our example demonstrates that social network analysis can be used to better understand the process of EOL communication. Social network analysis can be expanded to other areas of EOL research, such as EOL decision-making and health care teamwork. Copyright © 2018. Published by Elsevier Inc.

  6. NATbox: a network analysis toolbox in R.

    Science.gov (United States)

    Chavan, Shweta S; Bauer, Michael A; Scutari, Marco; Nagarajan, Radhakrishnan

    2009-10-08

    There has been recent interest in capturing the functional relationships (FRs) from high-throughput assays using suitable computational techniques. FRs elucidate the working of genes in concert as a system as opposed to independent entities hence may provide preliminary insights into biological pathways and signalling mechanisms. Bayesian structure learning (BSL) techniques and its extensions have been used successfully for modelling FRs from expression profiles. Such techniques are especially useful in discovering undocumented FRs, investigating non-canonical signalling mechanisms and cross-talk between pathways. The objective of the present study is to develop a graphical user interface (GUI), NATbox: Network Analysis Toolbox in the language R that houses a battery of BSL algorithms in conjunction with suitable statistical tools for modelling FRs in the form of acyclic networks from gene expression profiles and their subsequent analysis. NATbox is a menu-driven open-source GUI implemented in the R statistical language for modelling and analysis of FRs from gene expression profiles. It provides options to (i) impute missing observations in the given data (ii) model FRs and network structure from gene expression profiles using a battery of BSL algorithms and identify robust dependencies using a bootstrap procedure, (iii) present the FRs in the form of acyclic graphs for visualization and investigate its topological properties using network analysis metrics, (iv) retrieve FRs of interest from published literature. Subsequently, use these FRs as structural priors in BSL (v) enhance scalability of BSL across high-dimensional data by parallelizing the bootstrap routines. NATbox provides a menu-driven GUI for modelling and analysis of FRs from gene expression profiles. By incorporating readily available functions from existing R-packages, it minimizes redundancy and improves reproducibility, transparency and sustainability, characteristic of open-source environments

  7. Rural Health Networks: How Network Analysis Can Inform Patient Care and Organizational Collaboration in a Rural Breast Cancer Screening Network.

    Science.gov (United States)

    Prusaczyk, Beth; Maki, Julia; Luke, Douglas A; Lobb, Rebecca

    2018-04-15

    Rural health networks have the potential to improve health care quality and access. Despite this, the use of network analysis to study rural health networks is limited. The purpose of this study was to use network analysis to understand how a network of rural breast cancer care providers deliver services and to demonstrate the value of this methodology in this research area. Leaders at 47 Federally Qualified Health Centers and Rural Health Clinics across 10 adjacent rural counties were asked where they refer patients for mammograms or breast biopsies. These clinics and the 22 referral providers that respondents named comprised the network. The network was analyzed graphically and statistically with exponential random graph modeling. Most (96%, n = 45) of the clinics and referral sites (95%, n = 21) are connected to each other. Two clinics of the same type were 62% less likely to refer patients to the same providers as 2 clinics of different types (OR = 0.38, 95% CI = 0.29-0.50). Clinics in the same county have approximately 8 times higher odds of referring patients to the same providers compared to clinics in different counties (OR = 7.80, CI = 4.57-13.31). This study found that geographic location of resources is an important factor in rural health care providers' referral decisions and demonstrated the usefulness of network analysis for understanding rural health networks. These results can be used to guide delivery of patient care and strengthen the network by building resources that take location into account. © 2018 National Rural Health Association.

  8. An investigation and comparison on network performance analysis

    OpenAIRE

    Lanxiaopu, Mi

    2012-01-01

    This thesis is generally about network performance analysis. It contains two parts. The theory part summarizes what network performance is and inducts the methods of doing network performance analysis. To answer what network performance is, a study into what network services are is done. And based on the background research, there are two important network performance metrics: Network delay and Throughput should be included in network performance analysis. Among the methods of network a...

  9. Muscle networks: Connectivity analysis of EMG activity during postural control

    Science.gov (United States)

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-12-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

  10. Enabling dynamic network analysis through visualization in TVNViewer

    Directory of Open Access Journals (Sweden)

    Curtis Ross E

    2012-08-01

    Full Text Available Abstract Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer, a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space.

  11. Enabling dynamic network analysis through visualization in TVNViewer

    Science.gov (United States)

    2012-01-01

    Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space. PMID:22897913

  12. Investigating biofuels through network analysis

    International Nuclear Information System (INIS)

    Curci, Ylenia; Mongeau Ospina, Christian A.

    2016-01-01

    Biofuel policies are motivated by a plethora of political concerns related to energy security, environmental damages, and support of the agricultural sector. In response to this, much scientific work has chiefly focussed on analysing the biofuel domain and on giving policy advice and recommendations. Although innovation has been acknowledged as one of the key factors in sustainable and cost-effective biofuel development, there is an urgent need to investigate technological trajectories in the biofuel sector by starting from consistent data and appropriate methodological tools. To do so, this work proposes a procedure to select patent data unequivocally related to the investigated sector, it uses co-occurrence of technological terms to compute patent similarity and highlights content and interdependencies of biofuels technological trajectories by revealing hidden topics from unstructured patent text fields. The analysis suggests that there is a breaking trend towards modern generation biofuels and that innovators seem to focus increasingly on the ability of alternative energy sources to adapt to the transport/industrial sector. - Highlights: • Innovative effort is devoted to biofuels additives and modern biofuels technologies. • A breaking trend can be observed from the second half of the last decade. • A patent network is identified via text mining techniques that extract latent topics.

  13. Semantic web for integrated network analysis in biomedicine.

    Science.gov (United States)

    Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

    2009-03-01

    The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

  14. First demonstration of single-mode MCF transport network with crosstalk-aware in-service optical channel control

    DEFF Research Database (Denmark)

    Pulverer, K.; Tanaka, T.; Häbel, U.

    2017-01-01

    We demonstrate the first crosstalk-aware traffic engineering as a use case in a multicore fibre transport network. With the help of a software-defined network controller, modulation format and channel route are adaptively changed using programmable devices with XT monitors....

  15. Spatial analysis of bus transport networks using network theory

    Science.gov (United States)

    Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong

    2018-07-01

    In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison

  16. Weighted Complex Network Analysis of Pakistan Highways

    Directory of Open Access Journals (Sweden)

    Yasir Tariq Mohmand

    2013-01-01

    Full Text Available The structure and properties of public transportation networks have great implications in urban planning, public policies, and infectious disease control. This study contributes a weighted complex network analysis of travel routes on the national highway network of Pakistan. The network is responsible for handling 75 percent of the road traffic yet is largely inadequate, poor, and unreliable. The highway network displays small world properties and is assortative in nature. Based on the betweenness centrality of the nodes, the most important cities are identified as this could help in identifying the potential congestion points in the network. Keeping in view the strategic location of Pakistan, such a study is of practical importance and could provide opportunities for policy makers to improve the performance of the highway network.

  17. Noise Analysis studies with neural networks

    International Nuclear Information System (INIS)

    Seker, S.; Ciftcioglu, O.

    1996-01-01

    Noise analysis studies with neural network are aimed. Stochastic signals at the input of the network are used to obtain an algorithmic multivariate stochastic signal modeling. To this end, lattice modeling of a stochastic signal is performed to obtain backward residual noise sources which are uncorrelated among themselves. There are applied together with an additional input to the network to obtain an algorithmic model which is used for signal detection for early failure in plant monitoring. The additional input provides the information to the network to minimize the difference between the signal and the network's one-step-ahead prediction. A stochastic algorithm is used for training where the errors reflecting the measurement error during the training are also modelled so that fast and consistent convergence of network's weights is obtained. The lattice structure coupled to neural network investigated with measured signals from an actual power plant. (authors)

  18. CERN is first to demonstrate a 10 Gigabit/sec network

    CERN Multimedia

    CERN Press Office. Geneva

    2000-01-01

    CERN* has made another important step forward in high-speed computing and state of the art networking. On 15 September a Gigabyte System Network (GSN) network with a capacity of 10 Gbit per second ramped up successfully at CERN, connecting together computers from different computer companies (Compaq, IBM, SGI and Sun).

  19. Campus-Wide Networks: Three State-of-the-Art Demonstration Projects.

    Science.gov (United States)

    Chapman, Dale T.

    1986-01-01

    During the 1980's, the educational community has been keeping its eye hopefully on several campus-wide networking projects. Included are reports on progress in networks and networking at Carnegie Mellon University, the Massachussetts Institute of Technology (MIT), and at Brown University. (JN)

  20. Classification and Analysis of Computer Network Traffic

    OpenAIRE

    Bujlow, Tomasz

    2014-01-01

    Traffic monitoring and analysis can be done for multiple different reasons: to investigate the usage of network resources, assess the performance of network applications, adjust Quality of Service (QoS) policies in the network, log the traffic to comply with the law, or create realistic models of traffic for academic purposes. We define the objective of this thesis as finding a way to evaluate the performance of various applications in a high-speed Internet infrastructure. To satisfy the obje...

  1. Wireless Sensor Network Security Analysis

    OpenAIRE

    Hemanta Kumar Kalita; Avijit Kar

    2009-01-01

    The emergence of sensor networks as one of the dominant technology trends in the coming decades hasposed numerous unique challenges to researchers. These networks are likely to be composed of hundreds,and potentially thousands of tiny sensor nodes, functioning autonomously, and in many cases, withoutaccess to renewable energy resources. Cost constraints and the need for ubiquitous, invisibledeployments will result in small sized, resource-constrained sensor nodes. While the set of challenges ...

  2. Industrial entrepreneurial network: Structural and functional analysis

    Science.gov (United States)

    Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.

    2016-12-01

    Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.

  3. 3rd International Conference on Network Analysis

    CERN Document Server

    Kalyagin, Valery; Pardalos, Panos

    2014-01-01

    This volume compiles the major results of conference participants from the "Third International Conference in Network Analysis" held at the Higher School of Economics, Nizhny Novgorod in May 2013, with the aim to initiate further joint research among different groups. The contributions in this book cover a broad range of topics relevant to the theory and practice of network analysis, including the reliability of complex networks, software, theory, methodology, and applications.  Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network has brought together researchers, practitioners from numerous fields such as operations research, computer science, transportation, energy, biomedicine, computational neuroscience and social sciences. In addition, new approaches and computer environments such as parallel computing, grid computing, cloud computing, and quantum computing have helped to solve large scale...

  4. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Yang Dan

    2008-12-01

    Full Text Available Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation. The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  5. Service network design of bike sharing systems analysis and optimization

    CERN Document Server

    Vogel, Patrick

    2016-01-01

    This monograph presents a tactical planning approach for service network design in metropolitan areas. Designing the service network requires the suitable aggregation of demand data as well as the anticipation of operational relocation decisions. To this end, an integrated approach of data analysis and mathematical optimization is introduced. The book also includes a case study based on real-world data to demonstrate the benefit of the proposed service network design approach. The target audience comprises primarily research experts in the field of traffic engineering, but the book may also be beneficial for graduate students.

  6. Custom Ontologies for Expanded Network Analysis

    Science.gov (United States)

    2006-12-01

    for Expanded Network Analysis. In Visualising Network Information (pp. 6-1 – 6-10). Meeting Proceedings RTO-MP-IST-063, Paper 6. Neuilly-sur-Seine...Even to this day, current research groups are working to develop an approach that involves taking all available text, video, imagery and audio and

  7. Analysis of complex networks using aggressive abstraction.

    Energy Technology Data Exchange (ETDEWEB)

    Colbaugh, Richard; Glass, Kristin.; Willard, Gerald

    2008-10-01

    This paper presents a new methodology for analyzing complex networks in which the network of interest is first abstracted to a much simpler (but equivalent) representation, the required analysis is performed using the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit abstractions that are simultaneously dramatically simplifying and property preserving we call these aggressive abstractions -- and which can therefore be analyzed using the proposed approach. We then introduce and develop two forms of aggressive abstraction: 1.) finite state abstraction, in which dynamical networks with uncountable state spaces are modeled using finite state systems, and 2.) onedimensional abstraction, whereby high dimensional network dynamics are captured in a meaningful way using a single scalar variable. In each case, the property preserving nature of the abstraction process is rigorously established and efficient algorithms are presented for computing the abstraction. The considerable potential of the proposed approach to complex networks analysis is illustrated through case studies involving vulnerability analysis of technological networks and predictive analysis for social processes.

  8. Consistency analysis of network traffic repositories

    NARCIS (Netherlands)

    Lastdrager, Elmer; Lastdrager, E.E.H.; Pras, Aiko

    Traffic repositories with TCP/IP header information are very important for network analysis. Researchers often assume that such repositories reliably represent all traffic that has been flowing over the network; little thoughts are made regarding the consistency of these repositories. Still, for

  9. Boolean Factor Analysis by Attractor Neural Network

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.

    2007-01-01

    Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007

  10. Spectrum-Based and Collaborative Network Topology Analysis and Visualization

    Science.gov (United States)

    Hu, Xianlin

    2013-01-01

    Networks are of significant importance in many application domains, such as World Wide Web and social networks, which often embed rich topological information. Since network topology captures the organization of network nodes and links, studying network topology is very important to network analysis. In this dissertation, we study networks by…

  11. Analysis and Testing of Mobile Wireless Networks

    Science.gov (United States)

    Alena, Richard; Evenson, Darin; Rundquist, Victor; Clancy, Daniel (Technical Monitor)

    2002-01-01

    Wireless networks are being used to connect mobile computing elements in more applications as the technology matures. There are now many products (such as 802.11 and 802.11b) which ran in the ISM frequency band and comply with wireless network standards. They are being used increasingly to link mobile Intranet into Wired networks. Standard methods of analyzing and testing their performance and compatibility are needed to determine the limits of the technology. This paper presents analytical and experimental methods of determining network throughput, range and coverage, and interference sources. Both radio frequency (BE) domain and network domain analysis have been applied to determine wireless network throughput and range in the outdoor environment- Comparison of field test data taken under optimal conditions, with performance predicted from RF analysis, yielded quantitative results applicable to future designs. Layering multiple wireless network- sooners can increase performance. Wireless network components can be set to different radio frequency-hopping sequences or spreading functions, allowing more than one sooner to coexist. Therefore, we ran multiple 802.11-compliant systems concurrently in the same geographical area to determine interference effects and scalability, The results can be used to design of more robust networks which have multiple layers of wireless data communication paths and provide increased throughput overall.

  12. Demonstration of innovative techniques for work zone safety data analysis

    Science.gov (United States)

    2009-07-15

    Based upon the results of the simulator data analysis, additional future research can be : identified to validate the driving simulator in terms of similarities with Ohio work zones. For : instance, the speeds observed in the simulator were greater f...

  13. Complex Network Analysis of Guangzhou Metro

    Directory of Open Access Journals (Sweden)

    Yasir Tariq Mohmand

    2015-11-01

    Full Text Available The structure and properties of public transportation networks can provide suggestions for urban planning and public policies. This study contributes a complex network analysis of the Guangzhou metro. The metro network has 236 kilometers of track and is the 6th busiest metro system of the world. In this paper topological properties of the network are explored. We observed that the network displays small world properties and is assortative in nature. The network possesses a high average degree of 17.5 with a small diameter of 5. Furthermore, we also identified the most important metro stations based on betweenness and closeness centralities. These could help in identifying the probable congestion points in the metro system and provide policy makers with an opportunity to improve the performance of the metro system.

  14. Extending Stochastic Network Calculus to Loss Analysis

    Directory of Open Access Journals (Sweden)

    Chao Luo

    2013-01-01

    Full Text Available Loss is an important parameter of Quality of Service (QoS. Though stochastic network calculus is a very useful tool for performance evaluation of computer networks, existing studies on stochastic service guarantees mainly focused on the delay and backlog. Some efforts have been made to analyse loss by deterministic network calculus, but there are few results to extend stochastic network calculus for loss analysis. In this paper, we introduce a new parameter named loss factor into stochastic network calculus and then derive the loss bound through the existing arrival curve and service curve via this parameter. We then prove that our result is suitable for the networks with multiple input flows. Simulations show the impact of buffer size, arrival traffic, and service on the loss factor.

  15. Intelligent Network Flow Optimization (INFLO) prototype : Seattle small-scale demonstration plan.

    Science.gov (United States)

    2015-01-01

    This report describes the INFLO Prototype Small-Scale Demonstration to be performed in Seattle Washington. This demonstration is intended to demonstrate that the INFLO Prototype, previously demonstrated in a controlled environment, functions well in ...

  16. Computer network environment planning and analysis

    Science.gov (United States)

    Dalphin, John F.

    1989-01-01

    The GSFC Computer Network Environment provides a broadband RF cable between campus buildings and ethernet spines in buildings for the interlinking of Local Area Networks (LANs). This system provides terminal and computer linkage among host and user systems thereby providing E-mail services, file exchange capability, and certain distributed computing opportunities. The Environment is designed to be transparent and supports multiple protocols. Networking at Goddard has a short history and has been under coordinated control of a Network Steering Committee for slightly more than two years; network growth has been rapid with more than 1500 nodes currently addressed and greater expansion expected. A new RF cable system with a different topology is being installed during summer 1989; consideration of a fiber optics system for the future will begin soon. Summmer study was directed toward Network Steering Committee operation and planning plus consideration of Center Network Environment analysis and modeling. Biweekly Steering Committee meetings were attended to learn the background of the network and the concerns of those managing it. Suggestions for historical data gathering have been made to support future planning and modeling. Data Systems Dynamic Simulator, a simulation package developed at NASA and maintained at GSFC was studied as a possible modeling tool for the network environment. A modeling concept based on a hierarchical model was hypothesized for further development. Such a model would allow input of newly updated parameters and would provide an estimation of the behavior of the network.

  17. UMA/GAN network architecture analysis

    Science.gov (United States)

    Yang, Liang; Li, Wensheng; Deng, Chunjian; Lv, Yi

    2009-07-01

    This paper is to critically analyze the architecture of UMA which is one of Fix Mobile Convergence (FMC) solutions, and also included by the third generation partnership project(3GPP). In UMA/GAN network architecture, UMA Network Controller (UNC) is the key equipment which connects with cellular core network and mobile station (MS). UMA network could be easily integrated into the existing cellular networks without influencing mobile core network, and could provides high-quality mobile services with preferentially priced indoor voice and data usage. This helps to improve subscriber's experience. On the other hand, UMA/GAN architecture helps to integrate other radio technique into cellular network which includes WiFi, Bluetooth, and WiMax and so on. This offers the traditional mobile operators an opportunity to integrate WiMax technique into cellular network. In the end of this article, we also give an analysis of potential influence on the cellular core networks ,which is pulled by UMA network.

  18. Constructing an Intelligent Patent Network Analysis Method

    Directory of Open Access Journals (Sweden)

    Chao-Chan Wu

    2012-11-01

    Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

  19. Techniques for Intelligence Analysis of Networks

    National Research Council Canada - National Science Library

    Cares, Jeffrey R

    2005-01-01

    ...) there are significant intelligence analysis manifestations of these properties; and (4) a more satisfying theory of Networked Competition than currently exists for NCW/NCO is emerging from this research...

  20. Topological Analysis of Wireless Networks (TAWN)

    Science.gov (United States)

    2016-05-31

    19b. TELEPHONE NUMBER (Include area code) 31-05-2016 FINAL REPORT 12-02-2015 -- 31-05-2016 Topological Analysis of Wireless Networks (TAWN) Robinson...Release, Distribution Unlimited) N/A The goal of this project was to develop topological methods to detect and localize vulnerabilities of wireless... topology U U U UU 32 Michael Robinson 202-885-3681 Final Report: May 2016 Topological Analysis of Wireless Networks Principal Investigator: Prof. Michael

  1. Analysis of FOXO transcriptional networks

    NARCIS (Netherlands)

    van der Vos, K.E.

    2010-01-01

    The PI3K-PKB-FOXO signalling module plays a pivotal role in a wide variety of cellular processes, including proliferation, survival, differentiation and metabolism. Inappropriate activation of this network is frequently observed in human cancer and causes uncontrolled proliferation and survival. In

  2. Global Inventory and Analysis of Smart Grid Demonstration Projects

    Energy Technology Data Exchange (ETDEWEB)

    Mulder, W.; Kumpavat, K.; Faasen, C.; Verheij, F.; Vaessen, P [DNV KEMA Energy and Sustainability, Arnhem (Netherlands)

    2012-10-15

    As the key enabler of a more sustainable, economical and reliable energy system, the development of smart grids has received a great deal of attention in recent times. In many countries around the world the benefits of such a system have begun to be investigated through a number of demonstration projects. With such a vast array of projects it can be difficult to keep track of changes, and to understand which best practices are currently available with regard to smart grids. This report aims to address these issues through providing a comprehensive outlook on the current status of smart grid projects worldwide.

  3. Major component analysis of dynamic networks of physiologic organ interactions

    International Nuclear Information System (INIS)

    Liu, Kang K L; Ma, Qianli D Y; Ivanov, Plamen Ch; Bartsch, Ronny P

    2015-01-01

    The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function. (paper)

  4. NEXCADE: perturbation analysis for complex networks.

    Directory of Open Access Journals (Sweden)

    Gitanjali Yadav

    Full Text Available Recent advances in network theory have led to considerable progress in our understanding of complex real world systems and their behavior in response to external threats or fluctuations. Much of this research has been invigorated by demonstration of the 'robust, yet fragile' nature of cellular and large-scale systems transcending biology, sociology, and ecology, through application of the network theory to diverse interactions observed in nature such as plant-pollinator, seed-dispersal agent and host-parasite relationships. In this work, we report the development of NEXCADE, an automated and interactive program for inducing disturbances into complex systems defined by networks, focusing on the changes in global network topology and connectivity as a function of the perturbation. NEXCADE uses a graph theoretical approach to simulate perturbations in a user-defined manner, singly, in clusters, or sequentially. To demonstrate the promise it holds for broader adoption by the research community, we provide pre-simulated examples from diverse real-world networks including eukaryotic protein-protein interaction networks, fungal biochemical networks, a variety of ecological food webs in nature as well as social networks. NEXCADE not only enables network visualization at every step of the targeted attacks, but also allows risk assessment, i.e. identification of nodes critical for the robustness of the system of interest, in order to devise and implement context-based strategies for restructuring a network, or to achieve resilience against link or node failures. Source code and license for the software, designed to work on a Linux-based operating system (OS can be downloaded at http://www.nipgr.res.in/nexcade_download.html. In addition, we have developed NEXCADE as an OS-independent online web server freely available to the scientific community without any login requirement at http://www.nipgr.res.in/nexcade.html.

  5. A Network Text Analysis of David Ayer’s Fury

    Directory of Open Access Journals (Sweden)

    Starling David Hunter

    2015-12-01

    Full Text Available Network Text Analysis (NTA involves the creation of networks of words and/or concepts from linguistic data. Its key insight is that the position of words and concepts in a text network provides vital clues to the central and underlying themes of the text as a whole. Recent research has relied on inductive approaches to identify these themes. In this study we demonstrate a deductive approach that we apply to the screenplay of the 2014 World War II-era film Fury. Specifically, we first use genre expectations theory to establish prior expectations as to the key themes associated with war films. We then empirically test whether words and concepts associated with the most influentially-positioned nodes are consistent with themes common to the war-film genre. As predicted, we find that words and concepts associated with the least constrained nodes in the text network were significantly more likely to be associated with the war, action, and biography genres and significantly less likely to be associated with the mystery, science-fiction, fantasy, and film-noir genres. Keywords: content analysis, text analysis, network text analysis, semantic network analysis, film studies, screenplay, screenwriting, war movies, World War II, tanks

  6. Architecture Design and Experimental Platform Demonstration of Optical Network based on OpenFlow Protocol

    Science.gov (United States)

    Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang

    2016-02-01

    With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.

  7. 1st International Conference on Network Analysis

    CERN Document Server

    Kalyagin, Valery; Pardalos, Panos

    2013-01-01

    This volume contains a selection of contributions from the "First International Conference in Network Analysis," held at the University of Florida, Gainesville, on December 14-16, 2011. The remarkable diversity of fields that take advantage of Network Analysis makes the endeavor of gathering up-to-date material in a single compilation a useful, yet very difficult, task. The purpose of this volume is to overcome this difficulty by collecting the major results found by the participants and combining them in one easily accessible compilation. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network is bringing together researchers, practitioners and other scientific communities from numerous fields such as Operations Research, Computer Science, Transportation, Energy, Social Sciences, and more. The contributions not only come from different fields, but also cover a broad range of topics relevant to the...

  8. Artificial neural networks for plasma spectroscopy analysis

    International Nuclear Information System (INIS)

    Morgan, W.L.; Larsen, J.T.; Goldstein, W.H.

    1992-01-01

    Artificial neural networks have been applied to a variety of signal processing and image recognition problems. Of the several common neural models the feed-forward, back-propagation network is well suited for the analysis of scientific laboratory data, which can be viewed as a pattern recognition problem. The authors present a discussion of the basic neural network concepts and illustrate its potential for analysis of experiments by applying it to the spectra of laser produced plasmas in order to obtain estimates of electron temperatures and densities. Although these are high temperature and density plasmas, the neural network technique may be of interest in the analysis of the low temperature and density plasmas characteristic of experiments and devices in gaseous electronics

  9. Visualization and Analysis of Complex Covert Networks

    DEFF Research Database (Denmark)

    Memon, Bisharat

    systems that are covert and hence inherently complex. My Ph.D. is positioned within the wider framework of CrimeFighter project. The framework envisions a number of key knowledge management processes that are involved in the workflow, and the toolbox provides supporting tools to assist human end......This report discusses and summarize the results of my work so far in relation to my Ph.D. project entitled "Visualization and Analysis of Complex Covert Networks". The focus of my research is primarily on development of methods and supporting tools for visualization and analysis of networked......-users (intelligence analysts) in harvesting, filtering, storing, managing, structuring, mining, analyzing, interpreting, and visualizing data about offensive networks. The methods and tools proposed and discussed in this work can also be applied to analysis of more generic complex networks....

  10. Historical Network Analysis of the Web

    DEFF Research Database (Denmark)

    Brügger, Niels

    2013-01-01

    This article discusses some of the fundamental methodological challenges related to doing historical network analyses of the web based on material in web archives. Since the late 1990s many countries have established extensive national web archives, and software supported network analysis...... of the online web has for a number of years gained currency within Internet studies. However, the combination of these two phenomena—historical network analysis of material in web archives—can at best be characterized as an emerging new area of study. Most of the methodological challenges within this new area...... revolve around the specific nature of archived web material. On the basis of an introduction to the processes involved in web archiving as well as of the characteristics of archived web material, the article outlines and scrutinizes some of the major challenges which may arise when doing network analysis...

  11. Demonstration of Single-Mode Multicore Fiber Transport Network with Crosstalk-Aware In-Service Optical Path Control

    DEFF Research Database (Denmark)

    Tanaka, Takafumi; Pulverer, Klaus; Häbel, Ulrich

    2017-01-01

    transport network testbed and demonstrate an XT-aware traffic engineering scenario. With the help of a software-defined network (SDN) controller, the modulation format and optical path route are adaptively changed based on the monitored XT values by using programmable devices such as a real-time transponder......-capacity transmission, because inter-core crosstalk (XT) could be the main limiting factor for MCF transmission. In a real MCF network, the inter-core XT in a particular core is likely to change continuously as the optical paths in the adjacent cores are dynamically assigned to match the dynamic nature of the data...

  12. Intelligent Network Flow Optimization (INFLO) prototype : Seattle small-scale demonstration report.

    Science.gov (United States)

    2015-05-01

    This report describes the performance and results of the INFLO Prototype Small-Scale Demonstration. The purpose of : the Small-Scale Demonstration was to deploy the INFLO Prototype System to demonstrate its functionality and : performance in an opera...

  13. The International Trade Network: weighted network analysis and modelling

    International Nuclear Information System (INIS)

    Bhattacharya, K; Mukherjee, G; Manna, S S; Saramäki, J; Kaski, K

    2008-01-01

    Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN

  14. An examination of the relationship between athlete leadership and cohesion using social network analysis.

    Science.gov (United States)

    Loughead, Todd M; Fransen, Katrien; Van Puyenbroeck, Stef; Hoffmann, Matt D; De Cuyper, Bert; Vanbeselaere, Norbert; Boen, Filip

    2016-11-01

    Two studies investigated the structure of different athlete leadership networks and its relationship to cohesion using social network analysis. In Study 1, we examined the relationship between a general leadership quality network and task and social cohesion as measured by the Group Environment Questionnaire (GEQ). In Study 2, we investigated the leadership networks for four different athlete leadership roles (task, motivational, social and external) and their association with task and social cohesion networks. In Study 1, the results demonstrated that the general leadership quality network was positively related to task and social cohesion. The results from Study 2 indicated positive correlations between the four leadership networks and task and social cohesion networks. Further, the motivational leadership network emerged as the strongest predictor of the task cohesion network, while the social leadership network was the strongest predictor of the social cohesion network. The results complement a growing body of research indicating that athlete leadership has a positive association with cohesion.

  15. Demonstration study on shielding safety analysis code (VI)

    Energy Technology Data Exchange (ETDEWEB)

    Sawamura, Sadashi [Hokkaido Univ., Sapporo (Japan). Faculty of Engineering

    1999-03-01

    Dose evaluation for direct radiation and skyshine from nuclear fuel facilities is one of the environment evaluation items. This evaluation is carried out by using some shielding calculation codes. Because of extremely few benchmark data of skyshine, the calculation has to be performed very conservatively. Therefore, the benchmark data of skyshine and the well-investigated code for skyshine would be necessary to carry out the rational evaluation of nuclear facilities. The purpose of this steady is to obtain the benchmark data of skyshine and to investigate the calculation code for skyshine. In this fiscal year, the followings are investigated; (1) Construction and improvement of a pulsed radiation measurement system due to the gated counting method. (2) Using the system, carried out the radiation monitoring near and in the facility of 45 MeV Linear accelerator installed at Hokkaido University. (3) Simulation analysis of the photo-neutron production and the transport by using the EGS4 and MCNP code. (author)

  16. Geospatial analysis of food environment demonstrates associations with gestational diabetes.

    Science.gov (United States)

    Kahr, Maike K; Suter, Melissa A; Ballas, Jerasimos; Ramin, Susan M; Monga, Manju; Lee, Wesley; Hu, Min; Shope, Cindy D; Chesnokova, Arina; Krannich, Laura; Griffin, Emily N; Mastrobattista, Joan; Dildy, Gary A; Strehlow, Stacy L; Ramphul, Ryan; Hamilton, Winifred J; Aagaard, Kjersti M

    2016-01-01

    Gestational diabetes mellitus (GDM) is one of most common complications of pregnancy, with incidence rates varying by maternal age, race/ethnicity, obesity, parity, and family history. Given its increasing prevalence in recent decades, covariant environmental and sociodemographic factors may be additional determinants of GDM occurrence. We hypothesized that environmental risk factors, in particular measures of the food environment, may be a diabetes contributor. We employed geospatial modeling in a populous US county to characterize the association of the relative availability of fast food restaurants and supermarkets to GDM. Utilizing a perinatal database with >4900 encoded antenatal and outcome variables inclusive of ZIP code data, 8912 consecutive pregnancies were analyzed for correlations between GDM and food environment based on countywide food permit registration data. Linkage between pregnancies and food environment was achieved on the basis of validated 5-digit ZIP code data. The prevalence of supermarkets and fast food restaurants per 100,000 inhabitants for each ZIP code were gathered from publicly available food permit sources. To independently authenticate our findings with objective data, we measured hemoglobin A1c levels as a function of geospatial distribution of food environment in a matched subset (n = 80). Residence in neighborhoods with a high prevalence of fast food restaurants (fourth quartile) was significantly associated with an increased risk of developing GDM (relative to first quartile: adjusted odds ratio, 1.63; 95% confidence interval, 1.21-2.19). In multivariate analysis, this association held true after controlling for potential confounders (P = .002). Measurement of hemoglobin A1c levels in a matched subset were significantly increased in association with residence in a ZIP code with a higher fast food/supermarket ratio (n = 80, r = 0.251 P analysis, a relationship of food environment and risk for gestational diabetes was

  17. Network Anomaly Detection Based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Ali A. Ghorbani

    2008-11-01

    Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  18. Network Anomaly Detection Based on Wavelet Analysis

    Science.gov (United States)

    Lu, Wei; Ghorbani, Ali A.

    2008-12-01

    Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  19. Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis

    Directory of Open Access Journals (Sweden)

    Firoozeh Zare-Farashbandi

    2014-01-01

    Full Text Available Background: Co-authorship is one of the most tangible forms of research collaboration. A co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. The present research using the social network analysis studied co-authorship network of 681 articles published in Journal of Research in Medical Sciences (JRMS during 2008-2012. Materials and Methods: The study was carried out with the scientometrics approach and using co-authorship network analysis of authors. The topology of the co-authorship network of 681 published articles in JRMS between 2008 and 2012 was analyzed using macro-level metrics indicators of network analysis such as density, clustering coefficient, components and mean distance. In addition, in order to evaluate the performance of each authors and countries in the network, the micro-level indicators such as degree centrality, closeness centrality and betweenness centrality as well as productivity index were used. The UCINET and NetDraw softwares were used to draw and analyze the co-authorship network of the papers. Results: The assessment of the authors productivity in this journal showed that the first ranks were belonged to only five authors, respectively. Furthermore, analysis of the co-authorship of the authors in the network demonstrated that in the betweenness centrality index, three authors of them had the good position in the network. They can be considered as the network leaders able to control the flow of information in the network compared with the other members based on the shortest paths. On the other hand, the key role of the network according to the productivity and centrality indexes was belonged to Iran, Malaysia and United States of America. Conclusion: Co-authorship network of JRMS has the characteristics of a small world network. In addition, the theory of 6° separation is valid in this network was also true.

  20. Experimental Demonstration of Mixed Formats and Bit Rates Signal Allocation for Spectrum-flexible Optical Networking

    DEFF Research Database (Denmark)

    Borkowski, Robert; Karinou, Fotini; Angelou, Marianna

    2012-01-01

    We report on an extensive experimental study for adaptive allocation of 16-QAM and QPSK signals inside spectrum flexible heterogeneous superchannel. Physical-layer performance parameters are extracted for use in resource allocation mechanisms of future flexible networks....

  1. Experimental Demonstration of a Cognitive Optical Network for Reduction of Restoration Time

    DEFF Research Database (Denmark)

    Kachris, Christoforos; Klonidis, Dimitris; Francescon, Antonio

    2014-01-01

    This paper presents the implementation and performance evaluation of a cognitive heterogeneous optical network testbed. The testbed integrates the CMP, the data plane and the cognitive system and reduces by 48% the link restoration time.......This paper presents the implementation and performance evaluation of a cognitive heterogeneous optical network testbed. The testbed integrates the CMP, the data plane and the cognitive system and reduces by 48% the link restoration time....

  2. Social network analysis applied to team sports analysis

    CERN Document Server

    Clemente, Filipe Manuel; Mendes, Rui Sousa

    2016-01-01

    Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

  3. Fast network centrality analysis using GPUs

    Directory of Open Access Journals (Sweden)

    Shi Zhiao

    2011-05-01

    Full Text Available Abstract Background With the exploding volume of data generated by continuously evolving high-throughput technologies, biological network analysis problems are growing larger in scale and craving for more computational power. General Purpose computation on Graphics Processing Units (GPGPU provides a cost-effective technology for the study of large-scale biological networks. Designing algorithms that maximize data parallelism is the key in leveraging the power of GPUs. Results We proposed an efficient data parallel formulation of the All-Pairs Shortest Path problem, which is the key component for shortest path-based centrality computation. A betweenness centrality algorithm built upon this formulation was developed and benchmarked against the most recent GPU-based algorithm. Speedup between 11 to 19% was observed in various simulated scale-free networks. We further designed three algorithms based on this core component to compute closeness centrality, eccentricity centrality and stress centrality. To make all these algorithms available to the research community, we developed a software package gpu-fan (GPU-based Fast Analysis of Networks for CUDA enabled GPUs. Speedup of 10-50× compared with CPU implementations was observed for simulated scale-free networks and real world biological networks. Conclusions gpu-fan provides a significant performance improvement for centrality computation in large-scale networks. Source code is available under the GNU Public License (GPL at http://bioinfo.vanderbilt.edu/gpu-fan/.

  4. Sensitivity analysis of linear programming problem through a recurrent neural network

    Science.gov (United States)

    Das, Raja

    2017-11-01

    In this paper we study the recurrent neural network for solving linear programming problems. To achieve optimality in accuracy and also in computational effort, an algorithm is presented. We investigate the sensitivity analysis of linear programming problem through the neural network. A detailed example is also presented to demonstrate the performance of the recurrent neural network.

  5. Crawling Facebook for Social Network Analysis Purposes

    OpenAIRE

    Catanese, Salvatore A.; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo; Provetti, Alessandro

    2011-01-01

    We describe our work in the collection and analysis of massive data describing the connections between participants to online social networks. Alternative approaches to social network data collection are defined and evaluated in practice, against the popular Facebook Web site. Thanks to our ad-hoc, privacy-compliant crawlers, two large samples, comprising millions of connections, have been collected; the data is anonymous and organized as an undirected graph. We describe a set of tools that w...

  6. Automated Analysis of Security in Networking Systems

    DEFF Research Database (Denmark)

    Buchholtz, Mikael

    2004-01-01

    such networking systems are modelled in the process calculus LySa. On top of this programming language based formalism an analysis is developed, which relies on techniques from data and control ow analysis. These are techniques that can be fully automated, which make them an ideal basis for tools targeted at non...

  7. Network Analysis in Community Psychology: Looking Back, Looking Forward

    OpenAIRE

    Neal, Zachary P.; Neal, Jennifer Watling

    2017-01-01

    Highlights Network analysis is ideally suited for community psychology research because it focuses on context. Use of network analysis in community psychology is growing. Network analysis in community psychology has employed some potentially problematic practices. Recommended practices are identified to improve network analysis in community psychology.

  8. Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

    Science.gov (United States)

    Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

    2018-04-24

    Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

  9. Analysis of the experimental positron lifetime spectra by neural networks

    International Nuclear Information System (INIS)

    Avdic, S.; Chakarova, R.; Pazsit, I.

    2003-01-01

    This paper deals with the analysis of experimental positron lifetime spectra in polymer materials by using various algorithms of neural networks. A method based on the use of artificial neural networks for unfolding the mean lifetime and intensity of the spectral components of simulated positron lifetime spectra was previously suggested and tested on simulated data [Pazsit et al., Applied Surface Science, 149 (1998), 97]. In this work, the applicability of the method to the analysis of experimental positron spectra has been verified in the case of spectra from polymer materials with three components. It has been demonstrated that the backpropagation neural network can determine the spectral parameters with a high accuracy and perform the decomposition of lifetimes which differ by 10% or more. The backpropagation network has not been suitable for the identification of both the parameters and the number of spectral components. Therefore, a separate artificial neural network module has been designed to solve the classification problem. Module types based on self-organizing map and learning vector quantization algorithms have been tested. The learning vector quantization algorithm was found to have better performance and reliability. A complete artificial neural network analysis tool of positron lifetime spectra has been constructed to include a spectra classification module and parameter evaluation modules for spectra with a different number of components. In this way, both flexibility and high resolution can be achieved. (author)

  10. Distributed Finite Element Analysis Using a Transputer Network

    Science.gov (United States)

    Watson, James; Favenesi, James; Danial, Albert; Tombrello, Joseph; Yang, Dabby; Reynolds, Brian; Turrentine, Ronald; Shephard, Mark; Baehmann, Peggy

    1989-01-01

    The principal objective of this research effort was to demonstrate the extraordinarily cost effective acceleration of finite element structural analysis problems using a transputer-based parallel processing network. This objective was accomplished in the form of a commercially viable parallel processing workstation. The workstation is a desktop size, low-maintenance computing unit capable of supercomputer performance yet costs two orders of magnitude less. To achieve the principal research objective, a transputer based structural analysis workstation termed XPFEM was implemented with linear static structural analysis capabilities resembling commercially available NASTRAN. Finite element model files, generated using the on-line preprocessing module or external preprocessing packages, are downloaded to a network of 32 transputers for accelerated solution. The system currently executes at about one third Cray X-MP24 speed but additional acceleration appears likely. For the NASA selected demonstration problem of a Space Shuttle main engine turbine blade model with about 1500 nodes and 4500 independent degrees of freedom, the Cray X-MP24 required 23.9 seconds to obtain a solution while the transputer network, operated from an IBM PC-AT compatible host computer, required 71.7 seconds. Consequently, the $80,000 transputer network demonstrated a cost-performance ratio about 60 times better than the $15,000,000 Cray X-MP24 system.

  11. An improved algorithm for connectivity analysis of distribution networks

    International Nuclear Information System (INIS)

    Kansal, M.L.; Devi, Sunita

    2007-01-01

    In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks

  12. Performance analysis and improvement of WPAN MAC for home networks.

    Science.gov (United States)

    Mehta, Saurabh; Kwak, Kyung Sup

    2010-01-01

    The wireless personal area network (WPAN) is an emerging wireless technology for future short range indoor and outdoor communication applications. The IEEE 802.15.3 medium access control (MAC) is proposed to coordinate the access to the wireless medium among the competing devices, especially for short range and high data rate applications in home networks. In this paper we use analytical modeling to study the performance analysis of WPAN (IEEE 802.15.3) MAC in terms of throughput, efficient bandwidth utilization, and delay with various ACK policies under error channel condition. This allows us to introduce a K-Dly-ACK-AGG policy, payload size adjustment mechanism, and Improved Backoff algorithm to improve the performance of the WPAN MAC. Performance evaluation results demonstrate the impact of our improvements on network capacity. Moreover, these results can be very useful to WPAN application designers and protocol architects to easily and correctly implement WPAN for home networking.

  13. Performance Analysis and Improvement of WPAN MAC for Home Networks

    Directory of Open Access Journals (Sweden)

    Saurabh Mehta

    2010-03-01

    Full Text Available The wireless personal area network (WPAN is an emerging wireless technology for future short range indoor and outdoor communication applications. The IEEE 802.15.3 medium access control (MAC is proposed to coordinate the access to the wireless medium among the competing devices, especially for short range and high data rate applications in home networks. In this paper we use analytical modeling to study the performance analysis of WPAN (IEEE 802.15.3 MAC in terms of throughput, efficient bandwidth utilization, and delay with various ACK policies under error channel condition. This allows us to introduce a K-Dly-ACK-AGG policy, payload size adjustment mechanism, and Improved Backoff algorithm to improve the performance of the WPAN MAC. Performance evaluation results demonstrate the impact of our improvements on network capacity. Moreover, these results can be very useful to WPAN application designers and protocol architects to easily and correctly implement WPAN for home networking.

  14. Brain Network Analysis from High-Resolution EEG Signals

    Science.gov (United States)

    de Vico Fallani, Fabrizio; Babiloni, Fabio

    lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an

  15. Reliability analysis using network simulation

    International Nuclear Information System (INIS)

    1984-01-01

    A computer code that uses a dynamic, Monte Carlo modeling approach is Q-GERT (Graphical Evaluation and Review Technique--with Queueing), and the present study has demonstrated the feasibility of using Q-GERT for modeling time-dependent, unconditionally and conditionally linked phenomena that are characterized by arbitrarily selected probability distributions

  16. Demonstration of fully functional MIMO wireless LAN transmission over GI-MMF for in-building networks

    NARCIS (Netherlands)

    Zou, S.; Chen, H.; Huijskens, F.M.; Cao, Z.; Tangdiongga, E.; Koonen, A.M.J.

    2013-01-01

    We propose a low-cost optically-fed architecture capable of increasing the capacity and overall coverage of IEEE 802.11n MIMO WLAN system for in-building networks. A fully functional transmission over GI-MMF was demonstrated employing 2×3 MIMO configuration.

  17. Semantic network analysis of vaccine sentiment in online social media.

    Science.gov (United States)

    Kang, Gloria J; Ewing-Nelson, Sinclair R; Mackey, Lauren; Schlitt, James T; Marathe, Achla; Abbas, Kaja M; Swarup, Samarth

    2017-06-22

    To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage

  18. Social network analysis of study environment

    Directory of Open Access Journals (Sweden)

    Blaženka Divjak

    2010-06-01

    Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.

  19. Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations

    Science.gov (United States)

    Patrick, M. Clinton; Thaler, Stephen L.; Stevenson-Chavis, Katherine

    2006-01-01

    Neural Networks have been under examination for decades in many areas of research, with varying degrees of success and acceptance. Key goals of computer learning, rapid problem solution, and automatic adaptation have been elusive at best. This paper summarizes efforts at NASA's Marshall Space Flight Center harnessing such technology to autonomous space vehicle docking for the purpose of evaluating applicability to future missions.

  20. Demonstration of an application-aware resilience mechanism for dynamic heterogeneous networks

    NARCIS (Netherlands)

    Okonkwo, C.M.; Martin, R.; Ferrera, M.P.; Guild, K.M.; O'Mahony, M.; Everett, J.; Marciniak, M.

    2007-01-01

    Business uptake of IP-centric services has been strong and necessitates reliable, highly-available, high-quality Internet access. Real time services such as mission-critical broadcast video, video conferencing and voice over IP (VoIP) have low tolerance for short-term network outages. However,

  1. NAPS: Network Analysis of Protein Structures

    Science.gov (United States)

    Chakrabarty, Broto; Parekh, Nita

    2016-01-01

    Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue–residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein–protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201

  2. Information flow analysis of interactome networks.

    Directory of Open Access Journals (Sweden)

    Patrycja Vasilyev Missiuro

    2009-04-01

    Full Text Available Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein-protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we

  3. A statistical analysis of UK financial networks

    Science.gov (United States)

    Chu, J.; Nadarajah, S.

    2017-04-01

    In recent years, with a growing interest in big or large datasets, there has been a rise in the application of large graphs and networks to financial big data. Much of this research has focused on the construction and analysis of the network structure of stock markets, based on the relationships between stock prices. Motivated by Boginski et al. (2005), who studied the characteristics of a network structure of the US stock market, we construct network graphs of the UK stock market using same method. We fit four distributions to the degree density of the vertices from these graphs, the Pareto I, Fréchet, lognormal, and generalised Pareto distributions, and assess the goodness of fit. Our results show that the degree density of the complements of the market graphs, constructed using a negative threshold value close to zero, can be fitted well with the Fréchet and lognormal distributions.

  4. Emulation Platform for Cyber Analysis of Wireless Communication Network Protocols

    Energy Technology Data Exchange (ETDEWEB)

    Van Leeuwen, Brian P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Eldridge, John M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-11-01

    Wireless networking and mobile communications is increasing around the world and in all sectors of our lives. With increasing use, the density and complexity of the systems increase with more base stations and advanced protocols to enable higher data throughputs. The security of data transported over wireless networks must also evolve with the advances in technologies enabling more capable wireless networks. However, means for analysis of the effectiveness of security approaches and implementations used on wireless networks are lacking. More specifically a capability to analyze the lower-layer protocols (i.e., Link and Physical layers) is a major challenge. An analysis approach that incorporates protocol implementations without the need for RF emissions is necessary. In this research paper several emulation tools and custom extensions that enable an analysis platform to perform cyber security analysis of lower layer wireless networks is presented. A use case of a published exploit in the 802.11 (i.e., WiFi) protocol family is provided to demonstrate the effectiveness of the described emulation platform.

  5. Social Network Analysis Identifies Key Participants in Conservation Development.

    Science.gov (United States)

    Farr, Cooper M; Reed, Sarah E; Pejchar, Liba

    2018-05-01

    Understanding patterns of participation in private lands conservation, which is often implemented voluntarily by individual citizens and private organizations, could improve its effectiveness at combating biodiversity loss. We used social network analysis (SNA) to examine participation in conservation development (CD), a private land conservation strategy that clusters houses in a small portion of a property while preserving the remaining land as protected open space. Using data from public records for six counties in Colorado, USA, we compared CD participation patterns among counties and identified actors that most often work with others to implement CDs. We found that social network characteristics differed among counties. The network density, or proportion of connections in the network, varied from fewer than 2 to nearly 15%, and was higher in counties with smaller populations and fewer CDs. Centralization, or the degree to which connections are held disproportionately by a few key actors, was not correlated strongly with any county characteristics. Network characteristics were not correlated with the prevalence of wildlife-friendly design features in CDs. The most highly connected actors were biological and geological consultants, surveyors, and engineers. Our work demonstrates a new application of SNA to land-use planning, in which CD network patterns are examined and key actors are identified. For better conservation outcomes of CD, we recommend using network patterns to guide strategies for outreach and information dissemination, and engaging with highly connected actor types to encourage widespread adoption of best practices for CD design and stewardship.

  6. Network Analysis of Rodent Transcriptomes in Spaceflight

    Science.gov (United States)

    Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

    2017-01-01

    Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

  7. Complex network analysis of state spaces for random Boolean networks

    Energy Technology Data Exchange (ETDEWEB)

    Shreim, Amer [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Berdahl, Andrew [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Sood, Vishal [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Grassberger, Peter [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Paczuski, Maya [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada)

    2008-01-15

    We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 {<=} K {<=} 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2{sup N}, for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two.

  8. Complex network analysis of state spaces for random Boolean networks

    International Nuclear Information System (INIS)

    Shreim, Amer; Berdahl, Andrew; Sood, Vishal; Grassberger, Peter; Paczuski, Maya

    2008-01-01

    We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 ≤ K ≤ 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2 N , for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two

  9. Design Document for the Technology Demonstration of the Joint Network Defence and Management System (JNDMS) Project

    Science.gov (United States)

    2012-02-06

    Event Interface Custom ASCII JSS Client Y (Spectrum) 3.2 8 IT Infrastructure Performance Data/Vulnerability Assessment eHealth , Spectrum NSM...monitoring of infrastructure servers.) The Concord product line. Concord products ( eHealth and Spectrum) can provide both real-time and historical...Network and Systems Management (NSM) • Unicenter Asset Management • Spectrum • eHealth • Centennial Discovery Table 12 summarizes the the role of

  10. Northern emporia and maritime networks. Modelling past communication using archaeological network analysis

    DEFF Research Database (Denmark)

    Sindbæk, Søren Michael

    2015-01-01

    preserve patterns of thisinteraction. Formal network analysis and modelling holds the potential to identify anddemonstrate such patterns, where traditional methods often prove inadequate. Thearchaeological study of communication networks in the past, however, calls for radically different analytical...... this is not a problem of network analysis, but network synthesis: theclassic problem of cracking codes or reconstructing black-box circuits. It is proposedthat archaeological approaches to network synthesis must involve a contextualreading of network data: observations arising from individual contexts, morphologies...

  11. Analysis of Return and Forward Links from STARS' Flight Demonstration 1

    Science.gov (United States)

    Gering, James A.

    2003-01-01

    Space-based Telemetry And Range Safety (STARS) is a Kennedy Space Center (KSC) led proof-of-concept demonstration, which utilizes NASA's space network of Tracking and Data Relay Satellites (TDRS) as a pathway for launch and mission related information streams. Flight Demonstration 1 concluded on July 15,2003 with the seventh flight of a Low Power Transmitter (LPT) a Command and Data Handler (C&DH), a twelve channel GPS receiver and associated power supplies and amplifiers. The equipment flew on NASA's F-I5 aircraft at the Dryden Flight Research Center located at Edwards Air Force Base in California. During this NASA-ASEE Faculty Fellowship, the author participated in the collection and analysis of data from the seven flights comprising Flight Demonstration 1. Specifically, the author examined the forward and return links bit energy E(sub B) (in Watt-seconds) divided by the ambient radio frequency noise N(sub 0) (in Watts / Hertz). E(sub b)/N(sub 0) is commonly thought of as a signal-to-noise parameter, which characterizes a particular received radio frequency (RF) link. Outputs from the data analysis include the construction of time lines for all flights, production of graphs of range safety values for all seven flights, histograms of range safety E(sub b)/N(sub 0) values in five dB increments, calculation of associated averages and standard deviations, production of graphs of range user E(sub b)/N(sub 0) values for the all flights, production of graphs of AGC's and E(sub b)/N(sub 0) estimates for flight 1, recorded onboard, transmitted directly to the launch head and transmitted through TDRS. The data and graphs are being used to draw conclusions related to a lower than expected signal strength seen in the range safety return link.

  12. Diversity Performance Analysis on Multiple HAP Networks

    Science.gov (United States)

    Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

    2015-01-01

    One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102

  13. Diversity Performance Analysis on Multiple HAP Networks

    Directory of Open Access Journals (Sweden)

    Feihong Dong

    2015-06-01

    Full Text Available One of the main design challenges in wireless sensor networks (WSNs is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV. In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF and cumulative distribution function (CDF of the received signal-to-noise ratio (SNR are derived. In addition, the average symbol error rate (ASER with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.

  14. Mixed Methods Analysis of Enterprise Social Networks

    DEFF Research Database (Denmark)

    Behrendt, Sebastian; Richter, Alexander; Trier, Matthias

    2014-01-01

    The increasing use of enterprise social networks (ESN) generates vast amounts of data, giving researchers and managerial decision makers unprecedented opportunities for analysis. However, more transparency about the available data dimensions and how these can be combined is needed to yield accurate...

  15. Nonlinear Time Series Analysis via Neural Networks

    Science.gov (United States)

    Volná, Eva; Janošek, Michal; Kocian, Václav; Kotyrba, Martin

    This article deals with a time series analysis based on neural networks in order to make an effective forex market [Moore and Roche, J. Int. Econ. 58, 387-411 (2002)] pattern recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history to adapt our trading system behaviour based on them.

  16. Reliability analysis using network simulation

    International Nuclear Information System (INIS)

    Engi, D.

    1985-01-01

    The models that can be used to provide estimates of the reliability of nuclear power systems operate at many different levels of sophistication. The least-sophisticated models treat failure processes that entail only time-independent phenomena (such as demand failure). More advanced models treat processes that also include time-dependent phenomena such as run failure and possibly repair. However, many of these dynamic models are deficient in some respects because they either disregard the time-dependent phenomena that cannot be expressed in closed-form analytic terms or because they treat these phenomena in quasi-static terms. The next level of modeling requires a dynamic approach that incorporates not only procedures for treating all significant time-dependent phenomena but also procedures for treating these phenomena when they are conditionally linked or characterized by arbitrarily selected probability distributions. The level of sophistication that is required is provided by a dynamic, Monte Carlo modeling approach. A computer code that uses a dynamic, Monte Carlo modeling approach is Q-GERT (Graphical Evaluation and Review Technique - with Queueing), and the present study had demonstrated the feasibility of using Q-GERT for modeling time-dependent, unconditionally and conditionally linked phenomena that are characterized by arbitrarily selected probability distributions

  17. Reliability Analysis Techniques for Communication Networks in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Lim, T. J.; Jang, S. C.; Kang, H. G.; Kim, M. C.; Eom, H. S.; Lee, H. J.

    2006-09-01

    The objectives of this project is to investigate and study existing reliability analysis techniques for communication networks in order to develop reliability analysis models for nuclear power plant's safety-critical networks. It is necessary to make a comprehensive survey of current methodologies for communication network reliability. Major outputs of this study are design characteristics of safety-critical communication networks, efficient algorithms for quantifying reliability of communication networks, and preliminary models for assessing reliability of safety-critical communication networks

  18. Time series analysis of temporal networks

    Science.gov (United States)

    Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

    2016-01-01

    A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue

  19. Network analysis for the visualization and analysis of qualitative data.

    Science.gov (United States)

    Pokorny, Jennifer J; Norman, Alex; Zanesco, Anthony P; Bauer-Wu, Susan; Sahdra, Baljinder K; Saron, Clifford D

    2018-03-01

    We present a novel manner in which to visualize the coding of qualitative data that enables representation and analysis of connections between codes using graph theory and network analysis. Network graphs are created from codes applied to a transcript or audio file using the code names and their chronological location. The resulting network is a representation of the coding data that characterizes the interrelations of codes. This approach enables quantification of qualitative codes using network analysis and facilitates examination of associations of network indices with other quantitative variables using common statistical procedures. Here, as a proof of concept, we applied this method to a set of interview transcripts that had been coded in 2 different ways and the resultant network graphs were examined. The creation of network graphs allows researchers an opportunity to view and share their qualitative data in an innovative way that may provide new insights and enhance transparency of the analytical process by which they reach their conclusions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  20. Capacity analysis of wireless mesh networks | Gumel | Nigerian ...

    African Journals Online (AJOL)

    ... number of nodes (n) in a linear topology. The degradation is found to be higher in a fully mesh network as a result of increase in interference and MAC layer contention in the network. Key words: Wireless mesh network (WMN), Adhoc network, Network capacity analysis, Bottleneck collision domain, Medium access control ...

  1. Capacity analysis of vehicular communication networks

    CERN Document Server

    Lu, Ning

    2013-01-01

    This SpringerBrief focuses on the network capacity analysis of VANETs, a key topic as fundamental guidance on design and deployment of VANETs is very limited. Moreover, unique characteristics of VANETs impose distinguished challenges on such an investigation. This SpringerBrief first introduces capacity scaling laws for wireless networks and briefly reviews the prior arts in deriving the capacity of VANETs. It then studies the unicast capacity considering the socialized mobility model of VANETs. With vehicles communicating based on a two-hop relaying scheme, the unicast capacity bound is deriv

  2. s-core network decomposition: A generalization of k-core analysis to weighted networks

    Science.gov (United States)

    Eidsaa, Marius; Almaas, Eivind

    2013-12-01

    A broad range of systems spanning biology, technology, and social phenomena may be represented and analyzed as complex networks. Recent studies of such networks using k-core decomposition have uncovered groups of nodes that play important roles. Here, we present s-core analysis, a generalization of k-core (or k-shell) analysis to complex networks where the links have different strengths or weights. We demonstrate the s-core decomposition approach on two random networks (ER and configuration model with scale-free degree distribution) where the link weights are (i) random, (ii) correlated, and (iii) anticorrelated with the node degrees. Finally, we apply the s-core decomposition approach to the protein-interaction network of the yeast Saccharomyces cerevisiae in the context of two gene-expression experiments: oxidative stress in response to cumene hydroperoxide (CHP), and fermentation stress response (FSR). We find that the innermost s-cores are (i) different from innermost k-cores, (ii) different for the two stress conditions CHP and FSR, and (iii) enriched with proteins whose biological functions give insight into how yeast manages these specific stresses.

  3. Successful Completion of FY18/Q1 ASC L2 Milestone 6355: Electrical Analysis Calibration Workflow Capability Demonstration.

    Energy Technology Data Exchange (ETDEWEB)

    Copps, Kevin D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    The Sandia Analysis Workbench (SAW) project has developed and deployed a production capability for SIERRA computational mechanics analysis workflows. However, the electrical analysis workflow capability requirements have only been demonstrated in early prototype states, with no real capability deployed for analysts’ use. This milestone aims to improve the electrical analysis workflow capability (via SAW and related tools) and deploy it for ongoing use. We propose to focus on a QASPR electrical analysis calibration workflow use case. We will include a number of new capabilities (versus today’s SAW), such as: 1) support for the XYCE code workflow component, 2) data management coupled to electrical workflow, 3) human-in-theloop workflow capability, and 4) electrical analysis workflow capability deployed on the restricted (and possibly classified) network at Sandia. While far from the complete set of capabilities required for electrical analysis workflow over the long term, this is a substantial first step toward full production support for the electrical analysts.

  4. Intentional risk management through complex networks analysis

    CERN Document Server

    Chapela, Victor; Moral, Santiago; Romance, Miguel

    2015-01-01

    This book combines game theory and complex networks to examine intentional technological risk through modeling. As information security risks are in constant evolution,  the methodologies and tools to manage them must evolve to an ever-changing environment. A formal global methodology is explained  in this book, which is able to analyze risks in cyber security based on complex network models and ideas extracted from the Nash equilibrium. A risk management methodology for IT critical infrastructures is introduced which provides guidance and analysis on decision making models and real situations. This model manages the risk of succumbing to a digital attack and assesses an attack from the following three variables: income obtained, expense needed to carry out an attack, and the potential consequences for an attack. Graduate students and researchers interested in cyber security, complex network applications and intentional risk will find this book useful as it is filled with a number of models, methodologies a...

  5. Experimental Demonstration of Coexistence of Microwave Wireless Communication and Power Transfer Technologies for Battery-Free Sensor Network Systems

    Directory of Open Access Journals (Sweden)

    Satoshi Yoshida

    2013-01-01

    Full Text Available This paper describes experimental demonstrations of a wireless power transfer system equipped with a microwave band communication function. Battery charging using the system is described to evaluate the possibility of the coexistence of both wireless power transfer and communication functions in the C-band. A battery-free wireless sensor network system is demonstrated, and a high-power rectifier for the system is also designed and evaluated in the S-band. We have confirmed that microwave wireless power transfer can coexist with communication function.

  6. Remote Earth Terminals in the Health, Education, Telecommunications Network. Satellite Technology Demonstration, Technical Report No. 0423.

    Science.gov (United States)

    Braunstein, Jean; And Others

    The major purpose of the Health, Education, Telecommunications experiment was to demonstrate the feasibility of distributing video materials to a large number of low-cost earth terminals located in rural areas. The receivers are of two types: one-way video receivers for the reception of video programs, and two-way voice/data terminals which permit…

  7. A Network Thermodynamic Approach to Compartmental Analysis

    Science.gov (United States)

    Mikulecky, D. C.; Huf, E. G.; Thomas, S. R.

    1979-01-01

    We introduce a general network thermodynamic method for compartmental analysis which uses a compartmental model of sodium flows through frog skin as an illustrative example (Huf and Howell, 1974a). We use network thermodynamics (Mikulecky et al., 1977b) to formulate the problem, and a circuit simulation program (ASTEC 2, SPICE2, or PCAP) for computation. In this way, the compartment concentrations and net fluxes between compartments are readily obtained for a set of experimental conditions involving a square-wave pulse of labeled sodium at the outer surface of the skin. Qualitative features of the influx at the outer surface correlate very well with those observed for the short circuit current under another similar set of conditions by Morel and LeBlanc (1975). In related work, the compartmental model is used as a basis for simulation of the short circuit current and sodium flows simultaneously using a two-port network (Mikulecky et al., 1977a, and Mikulecky et al., A network thermodynamic model for short circuit current transients in frog skin. Manuscript in preparation; Gary-Bobo et al., 1978). The network approach lends itself to computation of classic compartmental problems in a simple manner using circuit simulation programs (Chua and Lin, 1975), and it further extends the compartmental models to more complicated situations involving coupled flows and non-linearities such as concentration dependencies, chemical reaction kinetics, etc. PMID:262387

  8. Stability analysis for stochastic BAM nonlinear neural network with delays

    Science.gov (United States)

    Lv, Z. W.; Shu, H. S.; Wei, G. L.

    2008-02-01

    In this paper, stochastic bidirectional associative memory neural networks with constant or time-varying delays is considered. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, we derive several sufficient conditions in order to guarantee the global asymptotically stable in the mean square. Our investigation shows that the stochastic bidirectional associative memory neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities(LMIs). Hence, the global asymptotic stability of the stochastic bidirectional associative memory neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global asymptotic stability criteria.

  9. Stability analysis for stochastic BAM nonlinear neural network with delays

    International Nuclear Information System (INIS)

    Lv, Z W; Shu, H S; Wei, G L

    2008-01-01

    In this paper, stochastic bidirectional associative memory neural networks with constant or time-varying delays is considered. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, we derive several sufficient conditions in order to guarantee the global asymptotically stable in the mean square. Our investigation shows that the stochastic bidirectional associative memory neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities(LMIs). Hence, the global asymptotic stability of the stochastic bidirectional associative memory neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global asymptotic stability criteria

  10. Static Voltage Stability Analysis by Using SVM and Neural Network

    Directory of Open Access Journals (Sweden)

    Mehdi Hajian

    2013-01-01

    Full Text Available Voltage stability is an important problem in power system networks. In this paper, in terms of static voltage stability, and application of Neural Networks (NN and Supported Vector Machine (SVM for estimating of voltage stability margin (VSM and predicting of voltage collapse has been investigated. This paper considers voltage stability in power system in two parts. The first part calculates static voltage stability margin by Radial Basis Function Neural Network (RBFNN. The advantage of the used method is high accuracy in online detecting the VSM. Whereas the second one, voltage collapse analysis of power system is performed by Probabilistic Neural Network (PNN and SVM. The obtained results in this paper indicate, that time and number of training samples of SVM, are less than NN. In this paper, a new model of training samples for detection system, using the normal distribution load curve at each load feeder, has been used. Voltage stability analysis is estimated by well-know L and VSM indexes. To demonstrate the validity of the proposed methods, IEEE 14 bus grid and the actual network of Yazd Province are used.

  11. Multiplex network analysis of employee performance and employee social relationships

    Science.gov (United States)

    Cai, Meng; Wang, Wei; Cui, Ying; Stanley, H. Eugene

    2018-01-01

    In human resource management, employee performance is strongly affected by both formal and informal employee networks. Most previous research on employee performance has focused on monolayer networks that can represent only single categories of employee social relationships. We study employee performance by taking into account the entire multiplex structure of underlying employee social networks. We collect three datasets consisting of five different employee relationship categories in three firms, and predict employee performance using degree centrality and eigenvector centrality in a superimposed multiplex network (SMN) and an unfolded multiplex network (UMN). We use a quadratic assignment procedure (QAP) analysis and a regression analysis to demonstrate that the different categories of relationship are mutually embedded and that the strength of their impact on employee performance differs. We also use weighted/unweighted SMN/UMN to measure the predictive accuracy of this approach and find that employees with high centrality in a weighted UMN are more likely to perform well. Our results shed new light on how social structures affect employee performance.

  12. Safeguards Network Analysis Procedure (SNAP): overview

    International Nuclear Information System (INIS)

    Chapman, L.D; Engi, D.

    1979-08-01

    Nuclear safeguards systems provide physical protection and control of nuclear materials. The Safeguards Network Analysis Procedure (SNAP) provides a convenient and standard analysis methodology for the evaluation of physical protection system effectiveness. This is achieved through a standard set of symbols which characterize the various elements of safeguards systems and an analysis program to execute simulation models built using the SNAP symbology. The outputs provided by the SNAP simulation program supplements the safeguards analyst's evaluative capabilities and supports the evaluation of existing sites as well as alternative design possibilities. This paper describes the SNAP modeling technique and provides an example illustrating its use

  13. Combining network analysis with Cognitive Work Analysis: insights into social organisational and cooperation analysis.

    Science.gov (United States)

    Houghton, Robert J; Baber, Chris; Stanton, Neville A; Jenkins, Daniel P; Revell, Kirsten

    2015-01-01

    Cognitive Work Analysis (CWA) allows complex, sociotechnical systems to be explored in terms of their potential configurations. However, CWA does not explicitly analyse the manner in which person-to-person communication is performed in these configurations. Consequently, the combination of CWA with Social Network Analysis provides a means by which CWA output can be analysed to consider communication structure. The approach is illustrated through a case study of a military planning team. The case study shows how actor-to-actor and actor-to-function mapping can be analysed, in terms of centrality, to produce metrics of system structure under different operating conditions. In this paper, a technique for building social network diagrams from CWA is demonstrated.The approach allows analysts to appreciate the potential impact of organisational structure on a command system.

  14. Analysis of JET charge exchange spectra using neural networks

    International Nuclear Information System (INIS)

    Svensson, J.; Hellermann, M. von; Koenig, R.W.T.

    1999-01-01

    Active charge exchange spectra representing the local interaction of injected neutral beams and fully stripped impurity ions are hard to analyse due to strong blending with passive emission from the plasma edge. As a result, the deduced plasma parameters (e.g. ion temperature, rotation velocity, impurity density) cannot always be determined unambiguously. Also, the speed of the analysis is limited by the time consuming nonlinear least-squares minimization procedure. In practice, semi-manual analysis is necessary and fast, automatic analysis, based on currently used techniques, does not seem feasible. In this paper the development of a robust and accurate analysis procedure based on multi-layer perceptron (MLP) neural networks is described. This procedure is fully automatic and fast, thus enabling a real-time analysis of charge exchange spectra. Accuracy has been increased in several ways as compared to earlier straightforward neural network implementations and is comparable to a standard least-squares based analysis. Robustness is achieved by using a combination of different confidence measures. A novel technique for the creation of training data, suitable for high-dimensional inverse problems has been developed and used extensively. A new method for fast calculation of error bars directly from the hidden neurons in a MLP network is also described, and used as part of the confidence calculations. For demonstration purposes, a real-time ion temperature profile diagnostic based on this work has been implemented. (author)

  15. Principal component analysis networks and algorithms

    CERN Document Server

    Kong, Xiangyu; Duan, Zhansheng

    2017-01-01

    This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.

  16. Spontaneous brain network activity: Analysis of its temporal complexity

    Directory of Open Access Journals (Sweden)

    Mangor Pedersen

    2017-06-01

    Full Text Available The brain operates in a complex way. The temporal complexity underlying macroscopic and spontaneous brain network activity is still to be understood. In this study, we explored the brain’s complexity by combining functional connectivity, graph theory, and entropy analyses in 25 healthy people using task-free functional magnetic resonance imaging. We calculated the pairwise instantaneous phase synchrony between 8,192 brain nodes for a total of 200 time points. This resulted in graphs for which time series of clustering coefficients (the “cliquiness” of a node and participation coefficients (the between-module connectivity of a node were estimated. For these two network metrics, sample entropy was calculated. The procedure produced a number of results: (1 Entropy is higher for the participation coefficient than for the clustering coefficient. (2 The average clustering coefficient is negatively related to its associated entropy, whereas the average participation coefficient is positively related to its associated entropy. (3 The level of entropy is network-specific to the participation coefficient, but not to the clustering coefficient. High entropy for the participation coefficient was observed in the default-mode, visual, and motor networks. These results were further validated using an independent replication dataset. Our work confirms that brain networks are temporally complex. Entropy is a good candidate metric to explore temporal network alterations in diseases with paroxysmal brain disruptions, including schizophrenia and epilepsy. In recent years, connectomics has provided significant insights into the topological complexity of brain networks. However, the temporal complexity of brain networks still remains somewhat poorly understood. In this study we used entropy analysis to demonstrate that the properties of network segregation (the clustering coefficient and integration (the participation coefficient are temporally complex

  17. Service network analysis for agricultural mental health

    Directory of Open Access Journals (Sweden)

    Fuller Jeffrey D

    2009-05-01

    Full Text Available Abstract Background Farmers represent a subgroup of rural and remote communities at higher risk of suicide attributed to insecure economic futures, self-reliant cultures and poor access to health services. Early intervention models are required that tap into existing farming networks. This study describes service networks in rural shires that relate to the mental health needs of farming families. This serves as a baseline to inform service network improvements. Methods A network survey of mental health related links between agricultural support, health and other human services in four drought declared shires in comparable districts in rural New South Wales, Australia. Mental health links covered information exchange, referral recommendations and program development. Results 87 agencies from 111 (78% completed a survey. 79% indicated that two thirds of their clients needed assistance for mental health related problems. The highest mean number of interagency links concerned information exchange and the frequency of these links between sectors was monthly to three monthly. The effectiveness of agricultural support and health sector links were rated as less effective by the agricultural support sector than by the health sector (p Conclusion Aligning with agricultural agencies is important to build effective mental health service pathways to address the needs of farming populations. Work is required to ensure that these agricultural support agencies have operational and effective links to primary mental health care services. Network analysis provides a baseline to inform this work. With interventions such as local mental health training and joint service planning to promote network development we would expect to see over time an increase in the mean number of links, the frequency in which these links are used and the rated effectiveness of these links.

  18. Social network analysis: Presenting an underused method for nursing research.

    Science.gov (United States)

    Parnell, James Michael; Robinson, Jennifer C

    2018-06-01

    This paper introduces social network analysis as a versatile method with many applications in nursing research. Social networks have been studied for years in many social science fields. The methods continue to advance but remain unknown to most nursing scholars. Discussion paper. English language and interpreted literature was searched from Ovid Healthstar, CINAHL, PubMed Central, Scopus and hard copy texts from 1965 - 2017. Social network analysis first emerged in nursing literature in 1995 and appears minimally through present day. To convey the versatility and applicability of social network analysis in nursing, hypothetical scenarios are presented. The scenarios are illustrative of three approaches to social network analysis and include key elements of social network research design. The methods of social network analysis are underused in nursing research, primarily because they are unknown to most scholars. However, there is methodological flexibility and epistemological versatility capable of supporting quantitative and qualitative research. The analytic techniques of social network analysis can add new insight into many areas of nursing inquiry, especially those influenced by cultural norms. Furthermore, visualization techniques associated with social network analysis can be used to generate new hypotheses. Social network analysis can potentially uncover findings not accessible through methods commonly used in nursing research. Social networks can be analysed based on individual-level attributes, whole networks and subgroups within networks. Computations derived from social network analysis may stand alone to answer a research question or incorporated as variables into robust statistical models. © 2018 John Wiley & Sons Ltd.

  19. Network value and optimum analysis on the mode of networked marketing in TV media

    Directory of Open Access Journals (Sweden)

    Xiao Dongpo

    2012-12-01

    Full Text Available Purpose: With the development of the networked marketing in TV media, it is important to do the research on network value and optimum analysis in this field.Design/methodology/approach: According to the research on the mode of networked marketing in TV media and Correlation theory, the essence of media marketing is creating, spreading and transferring values. The Participants of marketing value activities are in network, and value activities proceed in networked form. Network capability is important to TV media marketing activities.Findings: This article raises the direction of research of analysis and optimization about network based on the mode of networked marketing in TV media by studying TV media marketing Development Mechanism , network analysis and network value structure.

  20. Residential Fuel Cell Demonstration Handbook: National Rural Electric Cooperative Association Cooperative Research Network

    Energy Technology Data Exchange (ETDEWEB)

    Torrero, E.; McClelland, R.

    2002-07-01

    This report is a guide for rural electric cooperatives engaged in field testing of equipment and in assessing related application and market issues. Dispersed generation and its companion fuel cell technology have attracted increased interest by rural electric cooperatives and their customers. In addition, fuel cells are a particularly interesting source because their power quality, efficiency, and environmental benefits have now been coupled with major manufacturer development efforts. The overall effort is structured to measure the performance, durability, reliability, and maintainability of these systems, to identify promising types of applications and modes of operation, and to assess the related prospect for future use. In addition, technical successes and shortcomings will be identified by demonstration participants and manufacturers using real-world experience garnered under typical operating environments.

  1. Temporal sequence learning in winner-take-all networks of spiking neurons demonstrated in a brain-based device.

    Science.gov (United States)

    McKinstry, Jeffrey L; Edelman, Gerald M

    2013-01-01

    Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.

  2. NIF ICCS network design and loading analysis

    International Nuclear Information System (INIS)

    Tietbohl, G; Bryant, R

    1998-01-01

    The National Ignition Facility (NIF) is housed within a large facility about the size of two football fields. The Integrated Computer Control System (ICCS) is distributed throughout this facility and requires the integration of about 40,000 control points and over 500 video sources. This integration is provided by approximately 700 control computers distributed throughout the NIF facility and a network that provides the communication infrastructure. A main control room houses a set of seven computer consoles providing operator access and control of the various distributed front-end processors (FEPs). There are also remote workstations distributed within the facility that allow provide operator console functions while personnel are testing and troubleshooting throughout the facility. The operator workstations communicate with the FEPs which implement the localized control and monitoring functions. There are different types of FEPs for the various subsystems being controlled. This report describes the design of the NIF ICCS network and how it meets the traffic loads that will are expected and the requirements of the Sub-System Design Requirements (SSDR's). This document supersedes the earlier reports entitled Analysis of the National Ignition Facility Network, dated November 6, 1996 and The National Ignition Facility Digital Video and Control Network, dated July 9, 1996. For an overview of the ICCS, refer to the document NIF Integrated Computer Controls System Description (NIF-3738)

  3. Distinguishing manipulated stocks via trading network analysis

    Science.gov (United States)

    Sun, Xiao-Qian; Cheng, Xue-Qi; Shen, Hua-Wei; Wang, Zhao-Yang

    2011-10-01

    Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a trading network is constructed to characterize the relations among its investors. In trading networks, nodes represent investors and a directed link connects a stock seller to a buyer with the total trade size as the weight of the link, and the node strength is the sum of all edge weights of a node. For all these trading networks, we find that the node degree and node strength both have tails following a power-law distribution. Compared with non-manipulated stocks, manipulated stocks have a high lower bound of the power-law tail, a high average degree of the trading network and a low correlation between the price return and the seller-buyer ratio. These findings may help us to detect manipulated stocks.

  4. The Application of Social Network Analysis to Team Sports

    Science.gov (United States)

    Lusher, Dean; Robins, Garry; Kremer, Peter

    2010-01-01

    This article reviews how current social network analysis might be used to investigate individual and group behavior in sporting teams. Social network analysis methods permit researchers to explore social relations between team members and their individual-level qualities simultaneously. As such, social network analysis can be seen as augmenting…

  5. Analysis and visualization of citation networks

    CERN Document Server

    Zhao, Dangzhi

    2015-01-01

    Citation analysis-the exploration of reference patterns in the scholarly and scientific literature-has long been applied in a number of social sciences to study research impact, knowledge flows, and knowledge networks. It has important information science applications as well, particularly in knowledge representation and in information retrieval.Recent years have seen a burgeoning interest in citation analysis to help address research, management, or information service issues such as university rankings, research evaluation, or knowledge domain visualization. This renewed and growing interest

  6. An Intelligent technical analysis using neural network

    Directory of Open Access Journals (Sweden)

    Reza Raei

    2011-07-01

    Full Text Available Technical analysis has been one of the most popular methods for stock market predictions for the past few decades. There have been enormous technical analysis methods to study the behavior of stock market for different kinds of trading markets such as currency, commodity or stock. In this paper, we propose two different methods based on volume adjusted moving average and ease of movement for stock trading. These methods are used with and without generalized regression neural network methods and the results are compared with each other. The preliminary results on historical stock price of 20 firms indicate that there is no meaningful difference between various proposed models of this paper.

  7. Compartmentalization analysis using discrete fracture network models

    Energy Technology Data Exchange (ETDEWEB)

    La Pointe, P.R.; Eiben, T.; Dershowitz, W. [Golder Associates, Redmond, VA (United States); Wadleigh, E. [Marathon Oil Co., Midland, TX (United States)

    1997-08-01

    This paper illustrates how Discrete Fracture Network (DFN) technology can serve as a basis for the calculation of reservoir engineering parameters for the development of fractured reservoirs. It describes the development of quantitative techniques for defining the geometry and volume of structurally controlled compartments. These techniques are based on a combination of stochastic geometry, computational geometry, and graph the theory. The parameters addressed are compartment size, matrix block size and tributary drainage volume. The concept of DFN models is explained and methodologies to compute these parameters are demonstrated.

  8. The smart grid research network: Road map for Smart Grid research, development and demonstration up to 2020

    Energy Technology Data Exchange (ETDEWEB)

    Troi, A. [Technical Univ. of Denmark. DTU Electrical Engineering, DTU Risoe Campus, Roskilde (Denmark); Noerregaard Joergensen, B. [Syddansk Univ. (SDU), Odense (Denmark); Mahler Larsen, E. [Technical Univ. of Denmark. DTU Electrical Engineering, Kgs. Lyngby (Denmark)] [and others

    2013-01-15

    This road map is a result of part-recommendation no. 25 in 'MAIN REPORT - The Smart Grid Network's recommendations', written by the Smart Grid Network for the Danish Ministry of Climate, Energy and Building in October 2011. This part-recommendation states: ''Part-recommendation 25 - A road map for Smart Grid research, development and demonstration It is recommended that the electricity sector invite the Ministry to participate in the creation of a road map to ensure that solutions are implemented and coordinated with related policy areas. The sector should also establish a fast-acting working group with representatives from universities, distribution companies and the electric industry, in order to produce a mutual, binding schedule for the RDD of the Smart Grid in Denmark. Time prioritisation of part-recommendation: 2011-2012 Responsibility for implementation of part-recommendation: Universities, along with relevant electric-industry actors, should establish a working group for the completion of a consolidated road map by the end of 2012.'' In its work on this report, the Smart Grid Research Network has focused particularly on part-recommendations 26, 27 and 28 in 'MAIN REPORT - The Smart Grid Network's recommendations', which relate to strengthening and marketing the research infrastructure that will position Denmark as the global hub for Smart Grid development; strengthening basic research into the complex relationships in electric systems with large quantities of independent parties; and improved understanding of consumer behaviour and social economics. Naturally the work has spread to related areas along the way. The work has been conducted by the Smart Grid Research Network. (Author)

  9. The network researchers' network: A social network analysis of the IMP Group 1985-2006

    DEFF Research Database (Denmark)

    Henneberg, Stephan C. M.; Ziang, Zhizhong; Naudé, Peter

    The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

  10. Network Analysis of Time-Lapse Microscopy Recordings

    Directory of Open Access Journals (Sweden)

    Erik eSmedler

    2014-09-01

    Full Text Available Multicellular organisms rely on intercellular communication to regulate important cellular processes critical to life. To further our understanding of those processes there is a need to scrutinize dynamical signaling events and their functions in both cells and organisms. Here, we report a method and provide MATLAB code that analyzes time-lapse microscopy recordings to identify and characterize network structures within large cell populations, such as interconnected neurons. The approach is demonstrated using intracellular calcium (Ca2+ recordings in neural progenitors and cardiac myocytes, but could be applied to a wide variety of biosensors employed in diverse cell types and organisms. In this method, network structures are analyzed by applying cross-correlation signal processing and graph theory to single-cell recordings. The goal of the analysis is to determine if the single cell activity constitutes a network of interconnected cells and to decipher the properties of this network. The method can be applied in many fields of biology in which biosensors are used to monitor signaling events in living cells. Analyzing intercellular communication in cell ensembles can reveal essential network structures that provide important biological insights.

  11. Using principal component analysis for selecting network behavioral anomaly metrics

    Science.gov (United States)

    Gregorio-de Souza, Ian; Berk, Vincent; Barsamian, Alex

    2010-04-01

    This work addresses new approaches to behavioral analysis of networks and hosts for the purposes of security monitoring and anomaly detection. Most commonly used approaches simply implement anomaly detectors for one, or a few, simple metrics and those metrics can exhibit unacceptable false alarm rates. For instance, the anomaly score of network communication is defined as the reciprocal of the likelihood that a given host uses a particular protocol (or destination);this definition may result in an unrealistically high threshold for alerting to avoid being flooded by false positives. We demonstrate that selecting and adapting the metrics and thresholds, on a host-by-host or protocol-by-protocol basis can be done by established multivariate analyses such as PCA. We will show how to determine one or more metrics, for each network host, that records the highest available amount of information regarding the baseline behavior, and shows relevant deviances reliably. We describe the methodology used to pick from a large selection of available metrics, and illustrate a method for comparing the resulting classifiers. Using our approach we are able to reduce the resources required to properly identify misbehaving hosts, protocols, or networks, by dedicating system resources to only those metrics that actually matter in detecting network deviations.

  12. Proof-of-Concept Demonstrations of a Flight Adjustment Logging and Communication Network

    Science.gov (United States)

    Underwood, Matthew C.; Merlino, Daniel K.; Carboneau, Lindsey M.; Wilson, C. Logan; Wilder, Andrew J.

    2016-01-01

    The National Airspace System is a highly complex system of systems within which a number of participants with widely varying business and operating models exist. From the airspace user's perspective, a means by which to operate flights in a more flexible and efficient manner is highly desired to meet their business objectives. From the air navigation service provider's viewpoint, there is a need for increasing the capacity of the airspace, while maintaining or increasing the levels of efficiency and safety that currently exist in order to meet the charter under which they operate. Enhancing the communication between airspace operators and users is essential in order to meet these demands. In the spring of 2015, a prototype system that implemented an airborne tool to optimize en-route flight paths for fuel and time savings was designed and tested. The system utilized in-flight Internet as a high-bandwidth data link to facilitate collaborative decision making between the flight deck and an airline dispatcher. The system was tested and demonstrated in a laboratory environment, as well as in-situ. Initial results from these tests indicate that this system is not only feasible, but could also serve as a growth path and testbed for future air traffic management concepts that rely on shared situational awareness through data exchange and electronic negotiation between multiple entities operating within the National Airspace System.

  13. Simultaneity Analysis In A Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Malović Miodrag

    2015-06-01

    Full Text Available An original wireless sensor network for vibration measurements was designed. Its primary purpose is modal analysis of vibrations of large structures. A number of experiments have been performed to evaluate the system, with special emphasis on the influence of different effects on simultaneity of data acquired from remote nodes, which is essential for modal analysis. One of the issues is that quartz crystal oscillators, which provide time reading on the devices, are optimized for use in the room temperature and exhibit significant frequency variations if operated outside the 20–30°C range. Although much research was performed to optimize algorithms of synchronization in wireless networks, the subject of temperature fluctuations was not investigated and discussed in proportion to its significance. This paper describes methods used to evaluate data simultaneity and some algorithms suitable for its improvement in small to intermediate size ad-hoc wireless sensor networks exposed to varying temperatures often present in on-site civil engineering measurements.

  14. Bayesian-network-based safety risk analysis in construction projects

    International Nuclear Information System (INIS)

    Zhang, Limao; Wu, Xianguo; Skibniewski, Miroslaw J.; Zhong, Jingbing; Lu, Yujie

    2014-01-01

    This paper presents a systemic decision support approach for safety risk analysis under uncertainty in tunnel construction. Fuzzy Bayesian Networks (FBN) is used to investigate causal relationships between tunnel-induced damage and its influential variables based upon the risk/hazard mechanism analysis. Aiming to overcome limitations on the current probability estimation, an expert confidence indicator is proposed to ensure the reliability of the surveyed data for fuzzy probability assessment of basic risk factors. A detailed fuzzy-based inference procedure is developed, which has a capacity of implementing deductive reasoning, sensitivity analysis and abductive reasoning. The “3σ criterion” is adopted to calculate the characteristic values of a triangular fuzzy number in the probability fuzzification process, and the α-weighted valuation method is adopted for defuzzification. The construction safety analysis progress is extended to the entire life cycle of risk-prone events, including the pre-accident, during-construction continuous and post-accident control. A typical hazard concerning the tunnel leakage in the construction of Wuhan Yangtze Metro Tunnel in China is presented as a case study, in order to verify the applicability of the proposed approach. The results demonstrate the feasibility of the proposed approach and its application potential. A comparison of advantages and disadvantages between FBN and fuzzy fault tree analysis (FFTA) as risk analysis tools is also conducted. The proposed approach can be used to provide guidelines for safety analysis and management in construction projects, and thus increase the likelihood of a successful project in a complex environment. - Highlights: • A systemic Bayesian network based approach for safety risk analysis is developed. • An expert confidence indicator for probability fuzzification is proposed. • Safety risk analysis progress is extended to entire life cycle of risk-prone events. • A typical

  15. A Demonstrative Analysis of News Articles Using Fairclough’s Critical Discourse Analysis Framework

    Directory of Open Access Journals (Sweden)

    Roy Randy Y. Briones

    2017-07-01

    Full Text Available This paper attempts to demonstrate Norman Fairclough’s Critical Discourse Analysis (CDA framework by conducting internal and external level analyses on two online news articles that report on the Moro Islamic Liberation Front’s (MILF submission of its findings on the “Mamasapano Incident” that happened in the Philippines in 2015. In performing analyses using this framework, the social context and background for these texts, as well as the relationship between the internal discourse features and the external social practices and structures in which the texts were produced are thoroughly examined. As a result, it can be noted that from the texts’ internal discourse features, the news articles portray ideological and social distinctions among social actors such as the Philippine Senate, the SAF troopers, the MILF, the MILF fighters, and the civilians. Moreover, from the viewpoint of the texts as being external social practices, the texts maintain institutional identities as news reports, but they also reveal some evaluative stance as exemplified by the adjectival phrases that the writers employed. Having both the internal and external features examined, it can be said that the way these texts were written seems to portray power relations that exist between the Philippine government and the MILF. Key words: Critical Discourse Analysis, discourse analysis, news articles, social practices, social structures, power relations

  16. Understanding resilience in industrial symbiosis networks: insights from network analysis.

    Science.gov (United States)

    Chopra, Shauhrat S; Khanna, Vikas

    2014-08-01

    Industrial symbiotic networks are based on the principles of ecological systems where waste equals food, to develop synergistic networks. For example, industrial symbiosis (IS) at Kalundborg, Denmark, creates an exchange network of waste, water, and energy among companies based on contractual dependency. Since most of the industrial symbiotic networks are based on ad-hoc opportunities rather than strategic planning, gaining insight into disruptive scenarios is pivotal for understanding the balance of resilience and sustainability and developing heuristics for designing resilient IS networks. The present work focuses on understanding resilience as an emergent property of an IS network via a network-based approach with application to the Kalundborg Industrial Symbiosis (KIS). Results from network metrics and simulated disruptive scenarios reveal Asnaes power plant as the most critical node in the system. We also observe a decrease in the vulnerability of nodes and reduction in single points of failure in the system, suggesting an increase in the overall resilience of the KIS system from 1960 to 2010. Based on our findings, we recommend design strategies, such as increasing diversity, redundancy, and multi-functionality to ensure flexibility and plasticity, to develop resilient and sustainable industrial symbiotic networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Using structural equation modeling for network meta-analysis.

    Science.gov (United States)

    Tu, Yu-Kang; Wu, Yun-Chun

    2017-07-14

    Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison

  18. A flood-based information flow analysis and network minimization method for gene regulatory networks.

    Science.gov (United States)

    Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

    2013-04-24

    Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.

  19. Stochastic analysis of complex reaction networks using binomial moment equations.

    Science.gov (United States)

    Barzel, Baruch; Biham, Ofer

    2012-09-01

    The stochastic analysis of complex reaction networks is a difficult problem because the number of microscopic states in such systems increases exponentially with the number of reactive species. Direct integration of the master equation is thus infeasible and is most often replaced by Monte Carlo simulations. While Monte Carlo simulations are a highly effective tool, equation-based formulations are more amenable to analytical treatment and may provide deeper insight into the dynamics of the network. Here, we present a highly efficient equation-based method for the analysis of stochastic reaction networks. The method is based on the recently introduced binomial moment equations [Barzel and Biham, Phys. Rev. Lett. 106, 150602 (2011)]. The binomial moments are linear combinations of the ordinary moments of the probability distribution function of the population sizes of the interacting species. They capture the essential combinatorics of the reaction processes reflecting their stoichiometric structure. This leads to a simple and transparent form of the equations, and allows a highly efficient and surprisingly simple truncation scheme. Unlike ordinary moment equations, in which the inclusion of high order moments is prohibitively complicated, the binomial moment equations can be easily constructed up to any desired order. The result is a set of equations that enables the stochastic analysis of complex reaction networks under a broad range of conditions. The number of equations is dramatically reduced from the exponential proliferation of the master equation to a polynomial (and often quadratic) dependence on the number of reactive species in the binomial moment equations. The aim of this paper is twofold: to present a complete derivation of the binomial moment equations; to demonstrate the applicability of the moment equations for a representative set of example networks, in which stochastic effects play an important role.

  20. Analysis of complex systems using neural networks

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1992-01-01

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

  1. Network-based analysis of proteomic profiles

    KAUST Repository

    Wong, Limsoon

    2016-01-26

    Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.

  2. Social sciences via network analysis and computation

    CERN Document Server

    Kanduc, Tadej

    2015-01-01

    In recent years information and communication technologies have gained significant importance in the social sciences. Because there is such rapid growth of knowledge, methods and computer infrastructure, research can now seamlessly connect interdisciplinary fields such as business process management, data processing and mathematics. This study presents some of the latest results, practices and state-of-the-art approaches in network analysis, machine learning, data mining, data clustering and classifications in the contents of social sciences. It also covers various real-life examples such as t

  3. Analysis of Time Delay Simulation in Networked Control System

    OpenAIRE

    Nyan Phyo Aung; Zaw Min Naing; Hla Myo Tun

    2016-01-01

    The paper presents a PD controller for the Networked Control Systems (NCS) with delay. The major challenges in this networked control system (NCS) are the delay of the data transmission throughout the communication network. The comparative performance analysis is carried out for different delays network medium. In this paper, simulation is carried out on Ac servo motor control system using CAN Bus as communication network medium. The True Time toolbox of MATLAB is used for simulation to analy...

  4. Models as Tools of Analysis of a Network Organisation

    Directory of Open Access Journals (Sweden)

    Wojciech Pająk

    2013-06-01

    Full Text Available The paper presents models which may be applied as tools of analysis of a network organisation. The starting point of the discussion is defining the following terms: supply chain and network organisation. Further parts of the paper present basic assumptions analysis of a network organisation. Then the study characterises the best known models utilised in analysis of a network organisation. The purpose of the article is to define the notion and the essence of network organizations and to present the models used for their analysis.

  5. A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

    Science.gov (United States)

    Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

    2018-02-01

    Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

  6. Early stage design and analysis of biorefinery networks

    DEFF Research Database (Denmark)

    Sin, Gürkan

    2013-01-01

    Recent work regarding biorefineries resulted in many competing concepts and technologies for conversion of renewable bio-based feedstock into many promising products including fuels, chemicals, materials, etc. The design of a biorefinery process requires, at its earlier stages, the selection...... of the process configuration which exhibits the best performances, for a given set of economical, technical and environmental criteria. To this end, we formulate a computer-aided framework as an enabling technology for early stage design and analysis of biorefineries. The tool represents different raw materials......, different products and different available technologies and proposes a conceptual (early stage) biorefinery network. This network can then be the basis for further detailed and rigorous model-based studies. In this talk, we demonstrate the application of the tool for generating an early stage optimal...

  7. Analysis and Reduction of Complex Networks Under Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Knio, Omar M

    2014-04-09

    This is a collaborative proposal that aims at developing new methods for the analysis and reduction of complex multiscale networks under uncertainty. The approach is based on combining methods of computational singular perturbation (CSP) and probabilistic uncertainty quantification. In deterministic settings, CSP yields asymptotic approximations of reduced-dimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty raises fundamentally new issues, particularly concerning its impact on the topology of slow manifolds, and means to represent and quantify associated variability. To address these challenges, this project uses polynomial chaos (PC) methods to reformulate uncertain network models, and to analyze them using CSP in probabilistic terms. Specific objectives include (1) developing effective algorithms that can be used to illuminate fundamental and unexplored connections among model reduction, multiscale behavior, and uncertainty, and (2) demonstrating the performance of these algorithms through applications to model problems.

  8. Analysis and Comparison of Typical Models within Distribution Network Design

    DEFF Research Database (Denmark)

    Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.

    Efficient and cost effective transportation and logistics plays a vital role in the supply chains of the modern world’s manufacturers. Global distribution of goods is a very complicated matter as it involves many different distinct planning problems. The focus of this presentation is to demonstrate...... a number of important issues which have been identified when addressing the Distribution Network Design problem from a modelling angle. More specifically, we present an analysis of the research which has been performed in utilizing operational research in developing and optimising distribution systems....

  9. Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios

    DEFF Research Database (Denmark)

    Manzano, M.; Marzo, J. L.; Calle, E.

    2012-01-01

    on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....

  10. Identifying changes in the support networks of end-of-life carers using social network analysis.

    Science.gov (United States)

    Leonard, Rosemary; Horsfall, Debbie; Noonan, Kerrie

    2015-06-01

    End-of-life caring is often associated with reduced social networks for both the dying person and for the carer. However, those adopting a community participation and development approach, see the potential for the expansion and strengthening of networks. This paper uses Knox, Savage and Harvey's definitions of three generations social network analysis to analyse the caring networks of people with a terminal illness who are being cared for at home and identifies changes in these caring networks that occurred over the period of caring. Participatory network mapping of initial and current networks was used in nine focus groups. The analysis used key concepts from social network analysis (size, density, transitivity, betweenness and local clustering) together with qualitative analyses of the group's reflections on the maps. The results showed an increase in the size of the networks and that ties between the original members of the network strengthened. The qualitative data revealed the importance between core and peripheral network members and the diverse contributions of the network members. The research supports the value of third generation social network analysis and the potential for end-of-life caring to build social capital. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  11. A Demonstration Marine Biodiversity Observation Network (MBON): Understanding Marine Life and its Role in Maintaining Ecosystem Services

    Science.gov (United States)

    Muller-Karger, F. E.; Iken, K.; Miller, R. J.; Duffy, J. E.; Chavez, F.; Montes, E.

    2016-02-01

    The U.S. Federal government (NOAA, NASA, BOEM, and the Smithsonian Institution), academic researchers, and private partners are laying the foundation for a Marine Biodiversity Observation Network (MBON). The goals of the network are to: 1) Observe and understand life, from microbes to whales, in different coastal and continental shelf habitats; 2) Define an efficient set of observations required for implementing a useful MBON; 3) Develop technology for biodiversity assessments including emerging environmental DNA (eDNA), remote sensing, and image analysis methods to coordinate with classical sampling; 4) Integrate and synthesize information in coordination with the Integrated Ocean Observing System (IOOS), the international Group on Earth Observations Biodiversity Observation Network(GEO BON), and the Ocean Biogeographic Information System (OBIS) sponsored by UNESCO's Intergovernmental Oceanographic Commission (IOC); and 5) Understand the linkages between marine biodiversity, ecosystem processes, and the social-economic context of a region. Pilot projects have been implemented within three NOAA National Marine Sanctuaries (Florida Keys, Monterey Bay, and Channel Islands), the wider Santa Barbara Channel, in the Chukchi Sea, and through the Smithsonian's Tennenbaum Marine Observatories Network (TMON) at several sites in the U.S. and collaborating countries. Together, these MBON sites encompass a wide range of marine environments, including deep sea, continental shelves, and coastal habitats including estuaries, wetlands, and coral reefs. The present MBON partners are open to growth of the MBON through additional collaborations. Given these initiatives, GEO BON is proposing an MBON effort that spans from pole to pole, with a pathfinder effort among countries in the Americas. By specializing in coastal ecosystems—where marine biodiversity and people are concentrated and interact most—the MBON and TMON initiatives aim to provide policymakers with the science to

  12. Integrated corridor management initiative : demonstration phase evaluation - Dallas technical capability analysis test plan.

    Science.gov (United States)

    This report presents the test plan for conducting the Technical Capability Analysis for the United States : Department of Transportation (U.S. DOT) evaluation of the Dallas U.S. 75 Integrated Corridor : Management (ICM) Initiative Demonstration. The ...

  13. Integrated corridor management initiative : demonstration phase evaluation, San Diego technical capability analysis test plan.

    Science.gov (United States)

    2012-08-01

    This report presents the test plan for conducting the Technical Capability Analysis for the United States Department of Transportation (U.S. DOT) evaluation of the San Diego Integrated Corridor Management (ICM) Initiative Demonstration. The ICM proje...

  14. Reliability analysis with linguistic data: An evidential network approach

    International Nuclear Information System (INIS)

    Zhang, Xiaoge; Mahadevan, Sankaran; Deng, Xinyang

    2017-01-01

    In practical applications of reliability assessment of a system in-service, information about the condition of a system and its components is often available in text form, e.g., inspection reports. Estimation of the system reliability from such text-based records becomes a challenging problem. In this paper, we propose a four-step framework to deal with this problem. In the first step, we construct an evidential network with the consideration of available knowledge and data. Secondly, we train a Naive Bayes text classification algorithm based on the past records. By using the trained Naive Bayes algorithm to classify the new records, we build interval basic probability assignments (BPA) for each new record available in text form. Thirdly, we combine the interval BPAs of multiple new records using an evidence combination approach based on evidence theory. Finally, we propagate the interval BPA through the evidential network constructed earlier to obtain the system reliability. Two numerical examples are used to demonstrate the efficiency of the proposed method. We illustrate the effectiveness of the proposed method by comparing with Monte Carlo Simulation (MCS) results. - Highlights: • We model reliability analysis with linguistic data using evidential network. • Two examples are used to demonstrate the efficiency of the proposed method. • We compare the results with Monte Carlo Simulation (MCS).

  15. Spectral Analysis Methods of Social Networks

    Directory of Open Access Journals (Sweden)

    P. G. Klyucharev

    2017-01-01

    Full Text Available Online social networks (such as Facebook, Twitter, VKontakte, etc. being an important channel for disseminating information are often used to arrange an impact on the social consciousness for various purposes - from advertising products or services to the full-scale information war thereby making them to be a very relevant object of research. The paper reviewed the analysis methods of social networks (primarily, online, based on the spectral theory of graphs. Such methods use the spectrum of the social graph, i.e. a set of eigenvalues of its adjacency matrix, and also the eigenvectors of the adjacency matrix.Described measures of centrality (in particular, centrality based on the eigenvector and PageRank, which reflect a degree of impact one or another user of the social network has. A very popular PageRank measure uses, as a measure of centrality, the graph vertices, the final probabilities of the Markov chain, whose matrix of transition probabilities is calculated on the basis of the adjacency matrix of the social graph. The vector of final probabilities is an eigenvector of the matrix of transition probabilities.Presented a method of dividing the graph vertices into two groups. It is based on maximizing the network modularity by computing the eigenvector of the modularity matrix.Considered a method for detecting bots based on the non-randomness measure of a graph to be computed using the spectral coordinates of vertices - sets of eigenvector components of the adjacency matrix of a social graph.In general, there are a number of algorithms to analyse social networks based on the spectral theory of graphs. These algorithms show very good results, but their disadvantage is the relatively high (albeit polynomial computational complexity for large graphs.At the same time it is obvious that the practical application capacity of the spectral graph theory methods is still underestimated, and it may be used as a basis to develop new methods.The work

  16. Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research

    Science.gov (United States)

    Grunspan, Daniel Z.; Wiggins, Benjamin L.; Goodreau, Steven M.

    2014-01-01

    Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA)…

  17. Enzymatic solubilisation and degradation of soybean fibre demonstrated by viscosity, fibre analysis and microscopy

    DEFF Research Database (Denmark)

    Ravn, Jonas Laukkonen; Martens, Helle Juel; Pettersson, Dan

    2015-01-01

    The effect of a commercial multienzyme product obtained by fermentation from Aspergillus aculeatus on soybean and soybean meal was investigated using viscosity measurements, dietary fibre component analysis and different microscopy techniques utilizing histochemical dyes and antibody labelling....... The results obtained demonstrated a strong viscosity reducing effect of the enzyme preparation on soluble galactomannan and xyloglucan polysaccharides and in addition non-starch polysaccharide analysis demonstrated a notable solubilisation of all polysaccharide constituents. The degradation...

  18. Comparing Social Network Analysis of Posts with Counting of Posts as a Measurement of Learners' Participation in Facebook Discussions

    Science.gov (United States)

    Lee, Hye Yeon; Lee, Hyeon Woo

    2016-01-01

    With the currently growing interest in social network services, many college courses use social network services as platforms for discussions, and a number of studies have been conducted on the use of social network analysis to measure students' participation in online discussions. This study aims to demonstrate the difference between counting…

  19. Analysis and monitoring design for networks

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, V.; Flanagan, D.; Rowan, T.; Batsell, S.

    1998-06-01

    The idea of applying experimental design methodologies to develop monitoring systems for computer networks is relatively novel even though it was applied in other areas such as meteorology, seismology, and transportation. One objective of a monitoring system should always be to collect as little data as necessary to be able to monitor specific parameters of the system with respect to assigned targets and objectives. This implies a purposeful monitoring where each piece of data has a reason to be collected and stored for future use. When a computer network system as large and complex as the Internet is the monitoring subject, providing an optimal and parsimonious observing system becomes even more important. Many data collection decisions must be made by the developers of a monitoring system. These decisions include but are not limited to the following: (1) The type data collection hardware and software instruments to be used; (2) How to minimize interruption of regular network activities during data collection; (3) Quantification of the objectives and the formulation of optimality criteria; (4) The placement of data collection hardware and software devices; (5) The amount of data to be collected in a given time period, how large a subset of the available data to collect during the period, the length of the period, and the frequency of data collection; (6) The determination of the data to be collected (for instance, selection of response and explanatory variables); (7) Which data will be retained and how long (i.e., data storage and retention issues); and (8) The cost analysis of experiments. Mathematical statistics, and, in particular, optimal experimental design methods, may be used to address the majority of problems generated by 3--7. In this study, the authors focus their efforts on topics 3--5.

  20. 6th International Conference on Network Analysis

    CERN Document Server

    Nikolaev, Alexey; Pardalos, Panos; Prokopyev, Oleg

    2017-01-01

    This valuable source for graduate students and researchers provides a comprehensive introduction to current theories and applications in optimization methods and network models. Contributions to this book are focused on new efficient algorithms and rigorous mathematical theories, which can be used to optimize and analyze mathematical graph structures with massive size and high density induced by natural or artificial complex networks. Applications to social networks, power transmission grids, telecommunication networks, stock market networks, and human brain networks are presented. Chapters in this book cover the following topics: Linear max min fairness Heuristic approaches for high-quality solutions Efficient approaches for complex multi-criteria optimization problems Comparison of heuristic algorithms New heuristic iterative local search Power in network structures Clustering nodes in random graphs Power transmission grid structure Network decomposition problems Homogeneity hypothesis testing Network analy...

  1. Artificial neural network for violation analysis

    International Nuclear Information System (INIS)

    Zhang, Z.; Polet, P.; Vanderhaegen, F.; Millot, P.

    2004-01-01

    Barrier removal (BR) is a safety-related violation, and it can be analyzed in terms of benefits, costs, and potential deficits. In order to allow designers to integrate BR into the risk analysis during the initial design phase or during re-design work, we propose a connectionist method integrating self-organizing maps (SOM). The basic SOM is an artificial neural network that, on the basis of the information contained in a multi-dimensional space, generates a space of lesser dimensions. Three algorithms--Unsupervised SOM, Supervised SOM, and Hierarchical SOM--have been developed to permit BR classification and prediction in terms of the different criteria. The proposed method can be used, on the one hand, to foresee/predict the possibility level of a new/changed barrier (prospective analysis), and on the other hand, to synthetically regroup/rearrange the BR of a given human-machine system (retrospective analysis). We applied this method to the BR analysis of an experimental railway simulator, and our preliminary results are presented here

  2. The Design and Analysis of Virtual Network Configuration for a Wireless Mobile ATM Network

    OpenAIRE

    Bush, Stephen F.

    1999-01-01

    This research concentrates on the design and analysis of an algorithm referred to as Virtual Network Configuration (VNC) which uses predicted future states of a system for faster network configuration and management. VNC is applied to the configuration of a wireless mobile ATM network. VNC is built on techniques from parallel discrete event simulation merged with constraints from real-time systems and applied to mobile ATM configuration and handoff. Configuration in a mobile network is a dyna...

  3. Graph theoretical analysis and application of fMRI-based brain network in Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    LIU Xue-na

    2012-08-01

    Full Text Available Alzheimer's disease (AD, a progressive neurodegenerative disease, is clinically characterized by impaired memory and many other cognitive functions. However, the pathophysiological mechanisms underlying the disease are not thoroughly understood. In recent years, using functional magnetic resonance imaging (fMRI as well as advanced graph theory based network analysis approach, several studies of patients with AD suggested abnormal topological organization in both global and regional properties of functional brain networks, specifically, as demonstrated by a loss of small-world network characteristics. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis. In this paper we introduce the essential concepts of complex brain networks theory, and review recent advances of the study on human functional brain networks in AD, especially focusing on the graph theoretical analysis of small-world network based on fMRI. We also propound the existent problems and research orientation.

  4. Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

    Science.gov (United States)

    Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio

    2013-01-01

    This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.

  5. Analysis of robustness of urban bus network

    Science.gov (United States)

    Tao, Ren; Yi-Fan, Wang; Miao-Miao, Liu; Yan-Jie, Xu

    2016-02-01

    In this paper, the invulnerability and cascade failures are discussed for the urban bus network. Firstly, three static models(bus stop network, bus transfer network, and bus line network) are used to analyse the structure and invulnerability of urban bus network in order to understand the features of bus network comprehensively. Secondly, a new way is proposed to study the invulnerability of urban bus network by modelling two layered networks, i.e., the bus stop-line network and the bus line-transfer network and then the interactions between different models are analysed. Finally, by modelling a new layered network which can reflect the dynamic passenger flows, the cascade failures are discussed. Then a new load redistribution method is proposed to study the robustness of dynamic traffic. In this paper, the bus network of Shenyang City which is one of the biggest cities in China, is taken as a simulation example. In addition, some suggestions are given to improve the urban bus network and provide emergency strategies when traffic congestion occurs according to the numerical simulation results. Project supported by the National Natural Science Foundation of China (Grant Nos. 61473073, 61374178, 61104074, and 61203329), the Fundamental Research Funds for the Central Universities (Grant Nos. N130417006, L1517004), and the Program for Liaoning Excellent Talents in University (Grant No. LJQ2014028).

  6. Method and tool for network vulnerability analysis

    Science.gov (United States)

    Swiler, Laura Painton [Albuquerque, NM; Phillips, Cynthia A [Albuquerque, NM

    2006-03-14

    A computer system analysis tool and method that will allow for qualitative and quantitative assessment of security attributes and vulnerabilities in systems including computer networks. The invention is based on generation of attack graphs wherein each node represents a possible attack state and each edge represents a change in state caused by a single action taken by an attacker or unwitting assistant. Edges are weighted using metrics such as attacker effort, likelihood of attack success, or time to succeed. Generation of an attack graph is accomplished by matching information about attack requirements (specified in "attack templates") to information about computer system configuration (contained in a configuration file that can be updated to reflect system changes occurring during the course of an attack) and assumed attacker capabilities (reflected in "attacker profiles"). High risk attack paths, which correspond to those considered suited to application of attack countermeasures given limited resources for applying countermeasures, are identified by finding "epsilon optimal paths."

  7. Highlights and Lessons from the EU CCS Demonstration Project Network: 13th International Conference on Greenhouse Gas Control Technologies, GHGT 2016. 14 November 2016 through 18 November 2016

    NARCIS (Netherlands)

    Kapetaki, Z.; Hetland, J.; Guenan, T. le; Mikunda, T.; Scowcroft, J.

    2017-01-01

    The European Carbon Capture and Storage (CCS) Demonstration Project Network (the “Network”) is currently composed of projects located in the Netherlands, Norway, Spain, and the UK. The goal of the Network is to accelerate deployment of CCS by sharing project development experiences about technology

  8. First field demonstration of cloud datacenter workflow automation employing dynamic optical transport network resources under OpenStack and OpenFlow orchestration.

    Science.gov (United States)

    Szyrkowiec, Thomas; Autenrieth, Achim; Gunning, Paul; Wright, Paul; Lord, Andrew; Elbers, Jörg-Peter; Lumb, Alan

    2014-02-10

    For the first time, we demonstrate the orchestration of elastic datacenter and inter-datacenter transport network resources using a combination of OpenStack and OpenFlow. Programmatic control allows a datacenter operator to dynamically request optical lightpaths from a transport network operator to accommodate rapid changes of inter-datacenter workflows.

  9. Network-Based Visual Analysis of Tabular Data

    Science.gov (United States)

    Liu, Zhicheng

    2012-01-01

    Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look…

  10. Analysis of Computer Network Information Based on "Big Data"

    Science.gov (United States)

    Li, Tianli

    2017-11-01

    With the development of the current era, computer network and large data gradually become part of the people's life, people use the computer to provide convenience for their own life, but at the same time there are many network information problems has to pay attention. This paper analyzes the information security of computer network based on "big data" analysis, and puts forward some solutions.

  11. Road Transport Network Analysis In Port-Harcourt Metropolics ...

    African Journals Online (AJOL)

    Road transport network contributes to the economy of an area as it connects points of origin to destinations. The thrust of this article therefore, is on the analysis of the road networks in Port – Harcourt metropolis with the aim of determining the connectivity of the road networks and the most accessible node. Consequently ...

  12. Analysis of Municipal Pipe Network Franchise Institution

    Science.gov (United States)

    Yong, Sun; Haichuan, Tian; Feng, Xu; Huixia, Zhou

    Franchise institution of municipal pipe network has some particularity due to the characteristic of itself. According to the exposition of Chinese municipal pipe network industry franchise institution, the article investigates the necessity of implementing municipal pipe network franchise institution in China, the role of government in the process and so on. And this offers support for the successful implementation of municipal pipe network franchise institution in China.

  13. Advanced functional network analysis in the geosciences: The pyunicorn package

    Science.gov (United States)

    Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

    2013-04-01

    Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

  14. Analysis of neural networks through base functions

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.

    Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

  15. Synchronization analysis of coloured delayed networks under ...

    Indian Academy of Sciences (India)

    This paper investigates synchronization of coloured delayed networks under decentralized pinning intermittent control. To begin with, the time delays are taken into account in the coloured networks. In addition, we propose a decentralized pinning intermittent control for coloured delayed networks, which is different from that ...

  16. A Social Network Analysis of Occupational Segregation

    DEFF Research Database (Denmark)

    Buhai, Ioan Sebastian; van der Leij, Marco

    We develop a social network model of occupational segregation between different social groups, generated by the existence of positive inbreeding bias among individuals from the same group. If network referrals are important for job search, then expected homophily in the contact network structure...

  17. Pareto distance for multi-layer network analysis

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2013-01-01

    services, e.g., Facebook, Twitter, LinkedIn and Foursquare. As a result, the analysis of on-line social networks requires a wider scope and, more technically speaking, models for the representation of this fragmented scenario. The recent introduction of more realistic layered models has however determined......Social Network Analysis has been historically applied to single networks, e.g., interaction networks between co-workers. However, the advent of on-line social network sites has emphasized the stratified structure of our social experience. Individuals usually spread their identities over multiple...

  18. An asymptotic analysis of closed queueing networks with branching populations

    OpenAIRE

    Bayer, N.; Coffman, E.G.; Kogan, Y.A.

    1995-01-01

    textabstractClosed queueing networks have proven to be valuable tools for system performance analysis. In this paper, we broaden the applications of such networks by incorporating populations of {em branching customers: whenever a customer completes service at some node of the network, it is replaced by N>=0 customers, each routed independently to a next node, where N has a given, possibly node-dependent branching distribution. Applications of these branching and queueing networks focus on {e...

  19. A system of recurrent neural networks for modularising, parameterising and dynamic analysis of cell signalling networks.

    Science.gov (United States)

    Samarasinghe, S; Ling, H

    parameters and protein concentrations similar to the original RNN system. Results thus demonstrated the reliability of the proposed RNN method for modelling relatively large networks by modularisation for practical settings. Advantages of the method are its ability to represent accurate continuous system dynamics and ease of: parameter estimation through training with data from a practical setting, model analysis (40% faster than ODE), fine tuning parameters when more data are available, sub-model extension when new elements and/or interactions come to light and model expansion with addition of sub-models. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Data Farming Process and Initial Network Analysis Capabilities

    Directory of Open Access Journals (Sweden)

    Gary Horne

    2016-01-01

    Full Text Available Data Farming, network applications and approaches to integrate network analysis and processes to the data farming paradigm are presented as approaches to address complex system questions. Data Farming is a quantified approach that examines questions in large possibility spaces using modeling and simulation. It evaluates whole landscapes of outcomes to draw insights from outcome distributions and outliers. Social network analysis and graph theory are widely used techniques for the evaluation of social systems. Incorporation of these techniques into the data farming process provides analysts examining complex systems with a powerful new suite of tools for more fully exploring and understanding the effect of interactions in complex systems. The integration of network analysis with data farming techniques provides modelers with the capability to gain insight into the effect of network attributes, whether the network is explicitly defined or emergent, on the breadth of the model outcome space and the effect of model inputs on the resultant network statistics.

  1. Privacy Breach Analysis in Social Networks

    Science.gov (United States)

    Nagle, Frank

    This chapter addresses various aspects of analyzing privacy breaches in social networks. We first review literature that defines three types of privacy breaches in social networks: interactive, active, and passive. We then survey the various network anonymization schemes that have been constructed to address these privacy breaches. After exploring these breaches and anonymization schemes, we evaluate a measure for determining the level of anonymity inherent in a network graph based on its topological structure. Finally, we close by emphasizing the difficulty of anonymizing social network data while maintaining usability for research purposes and offering areas for future work.

  2. Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

    Directory of Open Access Journals (Sweden)

    Chernoded Andrey

    2017-01-01

    Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

  3. The Analysis of User Behaviour of a Network Management Training Tool using a Neural Network

    Directory of Open Access Journals (Sweden)

    Helen Donelan

    2005-10-01

    Full Text Available A novel method for the analysis and interpretation of data that describes the interaction between trainee network managers and a network management training tool is presented. A simulation based approach is currently being used to train network managers, through the use of a simulated network. The motivation is to provide a tool for exposing trainees to a life like situation without disrupting a live network. The data logged by this system describes the detailed interaction between trainee network manager and simulated network. The work presented here provides an analysis of this interaction data that enables an assessment of the capabilities of the trainee network manager as well as an understanding of how the network management tasks are being approached. A neural network architecture is implemented in order to perform an exploratory data analysis of the interaction data. The neural network employs a novel form of continuous self-organisation to discover key features in the data and thus provide new insights into the learning and teaching strategies employed.

  4. Applied and computational harmonic analysis on graphs and networks

    Science.gov (United States)

    Irion, Jeff; Saito, Naoki

    2015-09-01

    In recent years, the advent of new sensor technologies and social network infrastructure has provided huge opportunities and challenges for analyzing data recorded on such networks. In the case of data on regular lattices, computational harmonic analysis tools such as the Fourier and wavelet transforms have well-developed theories and proven track records of success. It is therefore quite important to extend such tools from the classical setting of regular lattices to the more general setting of graphs and networks. In this article, we first review basics of graph Laplacian matrices, whose eigenpairs are often interpreted as the frequencies and the Fourier basis vectors on a given graph. We point out, however, that such an interpretation is misleading unless the underlying graph is either an unweighted path or cycle. We then discuss our recent effort of constructing multiscale basis dictionaries on a graph, including the Hierarchical Graph Laplacian Eigenbasis Dictionary and the Generalized Haar-Walsh Wavelet Packet Dictionary, which are viewed as generalizations of the classical hierarchical block DCTs and the Haar-Walsh wavelet packets, respectively, to the graph setting. Finally, we demonstrate the usefulness of our dictionaries by using them to simultaneously segment and denoise 1-D noisy signals sampled on regular lattices, a problem where classical tools have difficulty.

  5. Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.

    Science.gov (United States)

    Arampatzis, Georgios; Katsoulakis, Markos A; Pantazis, Yannis

    2015-01-01

    Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over the

  6. Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.

    Directory of Open Access Journals (Sweden)

    Georgios Arampatzis

    Full Text Available Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of

  7. State of the art applications of social network analysis

    CERN Document Server

    Can, Fazli; Polat, Faruk

    2014-01-01

    Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user

  8. Network analysis and synthesis a modern systems theory approach

    CERN Document Server

    Anderson, Brian D O

    2006-01-01

    Geared toward upper-level undergraduates and graduate students, this book offers a comprehensive look at linear network analysis and synthesis. It explores state-space synthesis as well as analysis, employing modern systems theory to unite the classical concepts of network theory. The authors stress passive networks but include material on active networks. They avoid topology in dealing with analysis problems and discuss computational techniques. The concepts of controllability, observability, and degree are emphasized in reviewing the state-variable description of linear systems. Explorations

  9. Syphilis Networks in Louisiana: An Analysis of Network Configuration and Disease Transmission

    Science.gov (United States)

    Desmarais, Catherine Theresa

    Background: In 2009, Louisiana had the highest rate of primary and secondary syphilis in the country. Recent partner notification approaches have been insufficient in addressing Louisiana's deeply entrenched areas of syphilis infection. Prior researchers have suggested that surveillance systems may benefit from utilizing social and spatial network analysis in syphilis control efforts. Objective: To expand the understanding of the spread of syphilis in Louisiana, and to add new tools to the state's case finding resources through the description of the characteristics of cases of early syphilis and their partners in Louisiana, the socio-sexual networks of these cases, and the geospatial clustering of cases and partners. Methods: Utilizing state surveillance data, all cases of primary, secondary, and early latent syphilis that were diagnosed in 2009 and data on their sexual or needle sharing partners were analyzed using a combination of descriptive, network, and geospatial measures. Results: In 2009, Louisiana experienced a high rate of heterosexual syphilis transmission. Within syphilis transmission networks, 50.8% of all cases were female and 84.2% of all cases were black. The average and median ages of males with reactive syphilis tests were higher than that of females in Louisiana, and in 88.9% of regions, older individuals were more likely to have a syphilis test than no test. A greater proportion of males (11.4%) refused to discuss partners than females (7.4%) and a greater proportion of males (5.5%) refused testing and prophylactic treatment than females (2.8%). No distinct patterns were seen in disease prevalence between regions based upon demographic data. Classic summary network measures such as density, degree, centrality, and betweenness provided little information on similarities and differences between the different regions in Louisiana. All measures indicated low density and extreme fragmentation of networks in Louisiana. The majority of network

  10. Centrality measures in temporal networks with time series analysis

    Science.gov (United States)

    Huang, Qiangjuan; Zhao, Chengli; Zhang, Xue; Wang, Xiaojie; Yi, Dongyun

    2017-05-01

    The study of identifying important nodes in networks has a wide application in different fields. However, the current researches are mostly based on static or aggregated networks. Recently, the increasing attention to networks with time-varying structure promotes the study of node centrality in temporal networks. In this paper, we define a supra-evolution matrix to depict the temporal network structure. With using of the time series analysis, the relationships between different time layers can be learned automatically. Based on the special form of the supra-evolution matrix, the eigenvector centrality calculating problem is turned into the calculation of eigenvectors of several low-dimensional matrices through iteration, which effectively reduces the computational complexity. Experiments are carried out on two real-world temporal networks, Enron email communication network and DBLP co-authorship network, the results of which show that our method is more efficient at discovering the important nodes than the common aggregating method.

  11. Reliability Analysis of Wireless Sensor Networks Using Markovian Model

    Directory of Open Access Journals (Sweden)

    Jin Zhu

    2012-01-01

    Full Text Available This paper investigates reliability analysis of wireless sensor networks whose topology is switching among possible connections which are governed by a Markovian chain. We give the quantized relations between network topology, data acquisition rate, nodes' calculation ability, and network reliability. By applying Lyapunov method, sufficient conditions of network reliability are proposed for such topology switching networks with constant or varying data acquisition rate. With the conditions satisfied, the quantity of data transported over wireless network node will not exceed node capacity such that reliability is ensured. Our theoretical work helps to provide a deeper understanding of real-world wireless sensor networks, which may find its application in the fields of network design and topology control.

  12. Neural Network Analysis of LEAP Energy Spectra

    Energy Technology Data Exchange (ETDEWEB)

    Holdridge, Robert E

    2002-09-10

    The Laser Electron Acceleration Project (LEAP) group has been conducting a proof of principle experiment on the acceleration of electrons with a pair of crossed laser beams. To date there has been no experimental verification of electron acceleration with crossed laser beams in a dielectric loaded vacuum, although the energy profile of an accelerated electron bunch has been well described by theory. The experiment is subject to unavoidable time dependent fluctuations in the independent variables. Changes in the experimental parameters can dramatically alter the beam profile incident near the focal plane of a high-resolution spectrometer located downstream from the accelerator cell. Neural networks (NNs) appear to provide an ideal tool for the positive determination of an acceleration event, being adaptable and able to handle highly complex nonlinear problems. Typical NNs under such conditions require a training set consisting of a representative data set along with ''answers'' which have been determined to be consistent with the variable state of the experimental parameters. A strategy of pattern recognition with respect to the status of independent variables can be employed to determine the signature characteristics of a laser perturbed electron bunch. Data cuts representing characteristics that were thought to be distinctive to accelerated beam profile images were implemented in the algorithm employed. Statistical analysis of the results of data cuts made on the energy profile images from the experiment is presented, as well as conclusions drawn from the results of this analysis. Finally, a discussion of future directions to be taken in this work is given including the orientation towards on-line, real-time analysis.

  13. Demonstration uncertainty/sensitivity analysis using the health and economic consequence model CRAC2

    International Nuclear Information System (INIS)

    Alpert, D.J.; Iman, R.L.; Johnson, J.D.; Helton, J.C.

    1985-01-01

    This paper summarizes a demonstration uncertainty/sensitivity analysis performed on the reactor accident consequence model CRAC2. The study was performed with uncertainty/sensitivity analysis techniques compiled as part of the MELCOR program. The principal objectives of the study were: 1) to demonstrate the use of the uncertainty/sensitivity analysis techniques on a health and economic consequence model, 2) to test the computer models which implement the techniques, 3) to identify possible difficulties in performing such an analysis, and 4) to explore alternative means of analyzing, displaying, and describing the results. Demonstration of the applicability of the techniques was the motivation for performing this study; thus, the results should not be taken as a definitive uncertainty analysis of health and economic consequences. Nevertheless, significant insights on health and economic consequence analysis can be drawn from the results of this type of study. Latin hypercube sampling (LHS), a modified Monte Carlo technique, was used in this study. LHS generates a multivariate input structure in which all the variables of interest are varied simultaneously and desired correlations between variables are preserved. LHS has been shown to produce estimates of output distribution functions that are comparable with results of larger random samples

  14. Exploratory social network analysis with Pajek. - 2nd ed.

    NARCIS (Netherlands)

    de Nooy, W.; Mrvar, A.; Batagelj, V.

    2011-01-01

    This is an extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications, and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software

  15. Experimental Demonstration and Theoretical Analysis of Slow Light in a Semiconductor Waveguide at GHz Frequencies

    DEFF Research Database (Denmark)

    Mørk, Jesper; Kjær, Rasmus; Poel, Mike van der

    2005-01-01

    Experimental demonstration and theoretical analysis of slow light in a semiconductor waveguide at GHz frequencies slow-down of light by a factor of two in a semiconductor waveguide at room temperature with a bandwidth of 16.7 GHz using the effect of coherent pulsations of the carrier density...

  16. Using Musical Intervals to Demonstrate Superposition of Waves and Fourier Analysis

    Science.gov (United States)

    LoPresto, Michael C.

    2013-01-01

    What follows is a description of a demonstration of superposition of waves and Fourier analysis using a set of four tuning forks mounted on resonance boxes and oscilloscope software to create, capture and analyze the waveforms and Fourier spectra of musical intervals.

  17. Competing definitions: a public policy analysis of the federal recreational fee demonstration program

    Science.gov (United States)

    Thomas A. E. More

    2003-01-01

    Problem definition theory specifies that however controls the definition of a problem is in a unique position to control debate over the issue, influence others, and determine the problem's place on the agenda. This paper uses a rhetorical analysis and a questionnaire survey of congressional aides to examine the federal Recreational Fee Demonstration Program....

  18. MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

    Science.gov (United States)

    Jang, Yeongjun; Yu, Namhee; Seo, Jihae; Kim, Sun; Lee, Sanghyuk

    2016-03-18

    Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. .

  19. Unified Tractable Model for Large-Scale Networks Using Stochastic Geometry: Analysis and Design

    KAUST Repository

    Afify, Laila H.

    2016-12-01

    MIMO schemes, describe the relation between the diverse network parameters and configurations, and study the impact of temporal interference correlation on the performance of large-scale networks. Finally, we investigate some interference management techniques by exploiting the proposed framework. The proposed framework is compared to the exact analysis as well as intensive Monte Carlo simulations to demonstrate the model accuracy. The developed work casts a thorough inclusive study that is beneficial to deepen the understanding of the stochastic deployment of the next-generation large-scale wireless networks and predict their performance.

  20. Network meta-analysis: an introduction for pharmacists.

    Science.gov (United States)

    Xu, Yina; Amiche, Mohamed Amine; Tadrous, Mina

    2018-05-21

    Network meta-analysis is a new tool used to summarize and compare studies for multiple interventions, irrespective of whether these interventions have been directly evaluated against each other. Network meta-analysis is quickly becoming the standard in conducting therapeutic reviews and clinical guideline development. However, little guidance is available to help pharmacists review network meta-analysis studies in their practice. Major institutions such as the Cochrane Collaboration, Agency for Healthcare Research and Quality, Canadian Agency for Drugs and Technologies in Health, and National Institute for Health and Care Excellence Decision Support Unit have endorsed utilizing network meta-analysis to establish therapeutic evidence and inform decision making. Our objective is to introduce this novel technique to pharmacy practitioners, and highlight key assumptions behind network meta-analysis studies.

  1. Application of OLAM network in X-ray spectral analysis

    International Nuclear Information System (INIS)

    Liu Yinbing; Zhou Rongsheng

    2001-01-01

    The author describes a new approach to the automatic radioisotope identification problem based on the use of OLAM network. Different from the traditional methods, the OLAM network takes the spectrum as a whole comparing its shape with the patterns learned during the training period of the network. It is found that the OLAM network, once adequately trained, is quite suitable to identify a given isotope present in a mixture of elements as well as the relative proportions of each identified substance. Preliminary results are good enough to consider OLAM network as powerful and simple tools in the automatic spectrum analysis

  2. Constructing Social Networks From Secondary Storage With Bulk Analysis Tools

    Science.gov (United States)

    2016-06-01

    soccer team. However, for that drive if the k-value was reduced by one members of the drive owner’s family started to emerge . The same can be said for...including suggestions for reducing this burden to Washington headquarters Services , Directorate for Information Operations and Reports, 1215 Jefferson...Network of Online Application Usernames 53 Figure 5.6 Demonstration of a Network of Soccer Teammates . . . . . . 55 Figure 5.7 Demonstration of a

  3. Integrative analysis of many weighted co-expression networks using tensor computation.

    Directory of Open Access Journals (Sweden)

    Wenyuan Li

    2011-06-01

    Full Text Available The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks.

  4. Feasibility and demonstration of a cloud-based RIID analysis system

    Energy Technology Data Exchange (ETDEWEB)

    Wright, Michael C., E-mail: wrightmc@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Hertz, Kristin L.; Johnson, William C. [Sandia National Laboratories, Livermore, CA 94551 (United States); Sword, Eric D.; Younkin, James R. [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Sadler, Lorraine E. [Sandia National Laboratories, Livermore, CA 94551 (United States)

    2015-06-01

    A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed. - Highlights: • A prototype cloud-based RIID analysis system was implemented and demonstrated. • A cloud-based system was shown to be feasible with currently available technology. • A system study identified the operational characteristics required by the users. • The system study showed that the user community could derive significant benefit. • An architecture was defined for field testing by users in relevant environments.

  5. Feasibility and demonstration of a cloud-based RIID analysis system

    International Nuclear Information System (INIS)

    Wright, Michael C.; Hertz, Kristin L.; Johnson, William C.; Sword, Eric D.; Younkin, James R.; Sadler, Lorraine E.

    2015-01-01

    A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed. - Highlights: • A prototype cloud-based RIID analysis system was implemented and demonstrated. • A cloud-based system was shown to be feasible with currently available technology. • A system study identified the operational characteristics required by the users. • The system study showed that the user community could derive significant benefit. • An architecture was defined for field testing by users in relevant environments

  6. Analysis of the airport network of India as a complex weighted network

    Science.gov (United States)

    Bagler, Ganesh

    2008-05-01

    Transportation infrastructure of a country is one of the most important indicators of its economic growth. Here we study the Airport Network of India (ANI) which represents India’s domestic civil aviation infrastructure as a complex network. We find that ANI, a network of domestic airports connected by air links, is a small-world network characterized by a truncated power-law degree distribution and has a signature of hierarchy. We investigate ANI as a weighted network to explore its various properties and compare them with their topological counterparts. The traffic in ANI, as in the World-wide Airport Network (WAN), is found to be accumulated on interconnected groups of airports and is concentrated between large airports. In contrast to WAN, ANI is found to be having disassortative mixing which is offset by the traffic dynamics. The analysis indicates possible mechanism of formation of a national transportation network, which is different from that on a global scale.

  7. WGCNA: an R package for weighted correlation network analysis.

    Science.gov (United States)

    Langfelder, Peter; Horvath, Steve

    2008-12-29

    Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

  8. Pluripotency gene network dynamics: System views from parametric analysis.

    Science.gov (United States)

    Akberdin, Ilya R; Omelyanchuk, Nadezda A; Fadeev, Stanislav I; Leskova, Natalya E; Oschepkova, Evgeniya A; Kazantsev, Fedor V; Matushkin, Yury G; Afonnikov, Dmitry A; Kolchanov, Nikolay A

    2018-01-01

    Multiple experimental data demonstrated that the core gene network orchestrating self-renewal and differentiation of mouse embryonic stem cells involves activity of Oct4, Sox2 and Nanog genes by means of a number of positive feedback loops among them. However, recent studies indicated that the architecture of the core gene network should also incorporate negative Nanog autoregulation and might not include positive feedbacks from Nanog to Oct4 and Sox2. Thorough parametric analysis of the mathematical model based on this revisited core regulatory circuit identified that there are substantial changes in model dynamics occurred depending on the strength of Oct4 and Sox2 activation and molecular complexity of Nanog autorepression. The analysis showed the existence of four dynamical domains with different numbers of stable and unstable steady states. We hypothesize that these domains can constitute the checkpoints in a developmental progression from naïve to primed pluripotency and vice versa. During this transition, parametric conditions exist, which generate an oscillatory behavior of the system explaining heterogeneity in expression of pluripotent and differentiation factors in serum ESC cultures. Eventually, simulations showed that addition of positive feedbacks from Nanog to Oct4 and Sox2 leads mainly to increase of the parametric space for the naïve ESC state, in which pluripotency factors are strongly expressed while differentiation ones are repressed.

  9. Reachability Analysis in Probabilistic Biological Networks.

    Science.gov (United States)

    Gabr, Haitham; Todor, Andrei; Dobra, Alin; Kahveci, Tamer

    2015-01-01

    Extra-cellular molecules trigger a response inside the cell by initiating a signal at special membrane receptors (i.e., sources), which is then transmitted to reporters (i.e., targets) through various chains of interactions among proteins. Understanding whether such a signal can reach from membrane receptors to reporters is essential in studying the cell response to extra-cellular events. This problem is drastically complicated due to the unreliability of the interaction data. In this paper, we develop a novel method, called PReach (Probabilistic Reachability), that precisely computes the probability that a signal can reach from a given collection of receptors to a given collection of reporters when the underlying signaling network is uncertain. This is a very difficult computational problem with no known polynomial-time solution. PReach represents each uncertain interaction as a bi-variate polynomial. It transforms the reachability problem to a polynomial multiplication problem. We introduce novel polynomial collapsing operators that associate polynomial terms with possible paths between sources and targets as well as the cuts that separate sources from targets. These operators significantly shrink the number of polynomial terms and thus the running time. PReach has much better time complexity than the recent solutions for this problem. Our experimental results on real data sets demonstrate that this improvement leads to orders of magnitude of reduction in the running time over the most recent methods. Availability: All the data sets used, the software implemented and the alignments found in this paper are available at http://bioinformatics.cise.ufl.edu/PReach/.

  10. Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

    Directory of Open Access Journals (Sweden)

    Fikret Emre eKapucu

    2012-06-01

    Full Text Available In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC, exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing statistics based on interspike interval (ISI histograms. Moreover, the algorithm calculates interspike interval thresholds for burst spikes as well as for pre-burst spikes and burst tails by evaluating the cumulative moving average and skewness of the ISI histogram. Because of the adaptive nature of the proposed algorithm, its analysis power is not limited by the type of neuronal cell network at hand. We demonstrate the functionality of our algorithm with two different types of microelectrode array (MEA data recorded from spontaneously active hESC-derived neuronal cell networks. The same data was also analyzed by two commonly employed burst detection algorithms and the differences in burst detection results are illustrated. The results demonstrate that our method is both adaptive to the firing statistics of the network and yields successful burst detection from the data. In conclusion, the proposed method is a potential tool for analyzing of hESC-derived neuronal cell networks and thus can be utilized in studies aiming to understand the development and functioning of human neuronal networks and as an analysis tool for in vitro drug screening and neurotoxicity assays.

  11. Network Analysis of Earth's Co-Evolving Geosphere and Biosphere

    Science.gov (United States)

    Hazen, R. M.; Eleish, A.; Liu, C.; Morrison, S. M.; Meyer, M.; Consortium, K. D.

    2017-12-01

    A fundamental goal of Earth science is the deep understanding of Earth's dynamic, co-evolving geosphere and biosphere through deep time. Network analysis of geo- and bio- `big data' provides an interactive, quantitative, and predictive visualization framework to explore complex and otherwise hidden high-dimension features of diversity, distribution, and change in the evolution of Earth's geochemistry, mineralogy, paleobiology, and biochemistry [1]. Networks also facilitate quantitative comparison of different geological time periods, tectonic settings, and geographical regions, as well as different planets and moons, through network metrics, including density, centralization, diameter, and transitivity.We render networks by employing data related to geographical, paragenetic, environmental, or structural relationships among minerals, fossils, proteins, and microbial taxa. An important recent finding is that the topography of many networks reflects parameters not explicitly incorporated in constructing the network. For example, networks for minerals, fossils, and protein structures reveal embedded qualitative time axes, with additional network geometries possibly related to extinction and/or other punctuation events (see Figure). Other axes related to chemical activities and volatile fugacities, as well as pressure and/or depth of formation, may also emerge from network analysis. These patterns provide new insights into the way planets evolve, especially Earth's co-evolving geosphere and biosphere. 1. Morrison, S.M. et al. (2017) Network analysis of mineralogical systems. American Mineralogist 102, in press. Figure Caption: A network of Phanerozoic Era fossil animals from the past 540 million years includes blue, red, and black circles (nodes) representing family-level taxa and grey lines (links) between coexisting families. Age information was not used in the construction of this network; nevertheless an intrinsic timeline is embedded in the network topology. In

  12. Topology design and performance analysis of an integrated communication network

    Science.gov (United States)

    Li, V. O. K.; Lam, Y. F.; Hou, T. C.; Yuen, J. H.

    1985-01-01

    A research study on the topology design and performance analysis for the Space Station Information System (SSIS) network is conducted. It is begun with a survey of existing research efforts in network topology design. Then a new approach for topology design is presented. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. The algorithm for generating subsets is described in detail, and various aspects of the overall design procedure are discussed. Two more efficient versions of this algorithm (applicable in specific situations) are also given. Next, two important aspects of network performance analysis: network reliability and message delays are discussed. A new model is introduced to study the reliability of a network with dependent failures. For message delays, a collection of formulas from existing research results is given to compute or estimate the delays of messages in a communication network without making the independence assumption. The design algorithm coded in PASCAL is included as an appendix.

  13. Applications of social network analysis to obesity: a systematic review.

    Science.gov (United States)

    Zhang, S; de la Haye, K; Ji, M; An, R

    2018-04-20

    People's health behaviours and outcomes can be profoundly shaped by the social networks they are embedded in. Based on graph theory, social network analysis is a research framework for the study of social interactions and the structure of these interactions among social actors. A literature search was conducted in PubMed and Web of Science for articles published until August 2017 that applied social network analysis to examine obesity and social networks. Eight studies (three cross-sectional and five longitudinal) conducted in the US (n = 6) and Australia (n = 2) were identified. Seven focused on adolescents' and one on adults' friendship networks. They examined structural features of these networks that were associated with obesity, including degree distribution, popularity, modularity maximization and K-clique percolation. All three cross-sectional studies that used exponential random graph models found individuals with similar body weight status and/or weight-related behaviour were more likely to share a network tie than individuals with dissimilar traits. Three longitudinal studies using stochastic actor-based models found friendship network characteristics influenced change in individuals' body weight status and/or weight-related behaviour over time. Future research should focus on diverse populations and types of social networks and identifying the mechanisms by which social networks influence obesity to inform network-based interventions. © 2018 World Obesity Federation.

  14. Why social network analysis is important to Air Force applications

    Science.gov (United States)

    Havig, Paul R.; McIntire, John P.; Geiselman, Eric; Mohd-Zaid, Fairul

    2012-06-01

    Social network analysis is a powerful tool used to help analysts discover relationships amongst groups of people as well as individuals. It is the mathematics behind such social networks as Facebook and MySpace. These networks alone cause a huge amount of data to be generated and the issue is only compounded once one adds in other electronic media such as e-mails and twitter. In this paper we outline the basics of social network analysis and how it may be used in current and future Air Force applications.

  15. Choosing a heuristic and root node for edge ordering in BDD-based network reliability analysis

    International Nuclear Information System (INIS)

    Mo, Yuchang; Xing, Liudong; Zhong, Farong; Pan, Zhusheng; Chen, Zhongyu

    2014-01-01

    In the Binary Decision Diagram (BDD)-based network reliability analysis, heuristics have been widely used to obtain a reasonably good ordering of edge variables. Orderings generated using different heuristics can lead to dramatically different sizes of BDDs, and thus dramatically different running times and memory usages for the analysis of the same network. Unfortunately, due to the nature of the ordering problem (i.e., being an NP-complete problem) no formal guidelines or rules are available for choosing a good heuristic or for choosing a high-performance root node to perform edge searching using a particular heuristic. In this work, we make novel contributions by proposing heuristic and root node selection methods based on the concept of boundary sets for the BDD-based network reliability analysis. Empirical studies show that the proposed selection methods can help to generate high-performance edge ordering for most of studied cases, enabling the efficient BDD-based reliability analysis of large-scale networks. The proposed methods are demonstrated on different types of networks, including square lattice networks, torus lattice networks and de Bruijn networks

  16. Passivity analysis for uncertain BAM neural networks with time delays and reaction-diffusions

    Science.gov (United States)

    Zhou, Jianping; Xu, Shengyuan; Shen, Hao; Zhang, Baoyong

    2013-08-01

    This article deals with the problem of passivity analysis for delayed reaction-diffusion bidirectional associative memory (BAM) neural networks with weight uncertainties. By using a new integral inequality, we first present a passivity condition for the nominal networks, and then extend the result to the case with linear fractional weight uncertainties. The proposed conditions are expressed in terms of linear matrix inequalities, and thus can be checked easily. Examples are provided to demonstrate the effectiveness of the proposed results.

  17. Demonstrating the use of web analytics and an online survey to understand user groups of a national network of river level data

    Science.gov (United States)

    Macleod, Christopher Kit; Braga, Joao; Arts, Koen; Ioris, Antonio; Han, Xiwu; Sripada, Yaji; van der Wal, Rene

    2016-04-01

    The number of local, national and international networks of online environmental sensors are rapidly increasing. Where environmental data are made available online for public consumption, there is a need to advance our understanding of the relationships between the supply of and the different demands for such information. Understanding how individuals and groups of users are using online information resources may provide valuable insights into their activities and decision making. As part of the 'dot.rural wikiRivers' project we investigated the potential of web analytics and an online survey to generate insights into the use of a national network of river level data from across Scotland. These sources of online information were collected alongside phone interviews with volunteers sampled from the online survey, and interviews with providers of online river level data; as part of a larger project that set out to help improve the communication of Scotland's online river data. Our web analytics analysis was based on over 100 online sensors which are maintained by the Scottish Environmental Protection Agency (SEPA). Through use of Google Analytics data accessed via the R Ganalytics package we assessed: if the quality of data provided by Google Analytics free service is good enough for research purposes; if we could demonstrate what sensors were being used, when and where; how the nature and pattern of sensor data may affect web traffic; and whether we can identify and profile these users based on information from traffic sources. Web analytics data consists of a series of quantitative metrics which capture and summarize various dimensions of the traffic to a certain web page or set of pages. Examples of commonly used metrics include the number of total visits to a site and the number of total page views. Our analyses of the traffic sources from 2009 to 2011 identified several different major user groups. To improve our understanding of how the use of this national

  18. Weighted Complex Network Analysis of Shanghai Rail Transit System

    Directory of Open Access Journals (Sweden)

    Yingying Xing

    2016-01-01

    Full Text Available With increasing passenger flows and construction scale, Shanghai rail transit system (RTS has entered a new era of networking operation. In addition, the structure and properties of the RTS network have great implications for urban traffic planning, design, and management. Thus, it is necessary to acquire their network properties and impacts. In this paper, the Shanghai RTS, as well as passenger flows, will be investigated by using complex network theory. Both the topological and dynamic properties of the RTS network are analyzed and the largest connected cluster is introduced to assess the reliability and robustness of the RTS network. Simulation results show that the distribution of nodes strength exhibits a power-law behavior and Shanghai RTS network shows a strong weighted rich-club effect. This study also indicates that the intentional attacks are more detrimental to the RTS network than to the random weighted network, but the random attacks can cause slightly more damage to the random weighted network than to the RTS network. Our results provide a richer view of complex weighted networks in real world and possibilities of risk analysis and policy decisions for the RTS operation department.

  19. Demonstration Analysis of Relationship Between R&D Investment and GDP

    Institute of Scientific and Technical Information of China (English)

    HAN Bo-tang; LIU Bai-shan; CHEN Keng

    2005-01-01

    To reveal the quantitative relationship between research and development (R&D) investment and gross domestic product (GDP) in China, we have demonstrated and analyzed the relationship between R&D investment and science and technology (S&T) progress, and based on a mount of S&T statistical data, have proceeded demonstration research of the relationship between R&D investment and GDP in China with Solow and vector auto regression (VAR) models. Cubic curve fitting and cross-correlation analysis of them with SPSS have shown that there is a strong synchronic relationship between R&D investment and GDP.

  20. Sensitivity of the Positive and Negative Syndrome Scale (PANSS) in Detecting Treatment Effects via Network Analysis.

    Science.gov (United States)

    Esfahlani, Farnaz Zamani; Sayama, Hiroki; Visser, Katherine Frost; Strauss, Gregory P

    2017-12-01

    Objective: The Positive and Negative Syndrome Scale is a primary outcome measure in clinical trials examining the efficacy of antipsychotic medications. Although the Positive and Negative Syndrome Scale has demonstrated sensitivity as a measure of treatment change in studies using traditional univariate statistical approaches, its sensitivity to detecting network-level changes in dynamic relationships among symptoms has yet to be demonstrated using more sophisticated multivariate analyses. In the current study, we examined the sensitivity of the Positive and Negative Syndrome Scale to detecting antipsychotic treatment effects as revealed through network analysis. Design: Participants included 1,049 individuals diagnosed with psychotic disorders from the Phase I portion of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study. Of these participants, 733 were clinically determined to be treatment-responsive and 316 were found to be treatment-resistant. Item level data from the Positive and Negative Syndrome Scale were submitted to network analysis, and macroscopic, mesoscopic, and microscopic network properties were evaluated for the treatment-responsive and treatment-resistant groups at baseline and post-phase I antipsychotic treatment. Results: Network analysis indicated that treatment-responsive patients had more densely connected symptom networks after antipsychotic treatment than did treatment-responsive patients at baseline, and that symptom centralities increased following treatment. In contrast, symptom networks of treatment-resistant patients behaved more randomly before and after treatment. Conclusions: These results suggest that the Positive and Negative Syndrome Scale is sensitive to detecting treatment effects as revealed through network analysis. Its findings also provide compelling new evidence that strongly interconnected symptom networks confer an overall greater probability of treatment responsiveness in patients with

  1. Validation of network communicability metrics for the analysis of brain structural networks.

    Directory of Open Access Journals (Sweden)

    Jennifer Andreotti

    Full Text Available Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

  2. Using Social Network Analysis to Assess Mentorship and Collaboration in a Public Health Network.

    Science.gov (United States)

    Petrescu-Prahova, Miruna; Belza, Basia; Leith, Katherine; Allen, Peg; Coe, Norma B; Anderson, Lynda A

    2015-08-20

    Addressing chronic disease burden requires the creation of collaborative networks to promote systemic changes and engage stakeholders. Although many such networks exist, they are rarely assessed with tools that account for their complexity. This study examined the structure of mentorship and collaboration relationships among members of the Healthy Aging Research Network (HAN) using social network analysis (SNA). We invited 97 HAN members and partners to complete an online social network survey that included closed-ended questions about HAN-specific mentorship and collaboration during the previous 12 months. Collaboration was measured by examining the activity of the network on 6 types of products: published articles, in-progress manuscripts, grant applications, tools, research projects, and presentations. We computed network-level measures such as density, number of components, and centralization to assess the cohesiveness of the network. Sixty-three respondents completed the survey (response rate, 65%). Responses, which included information about collaboration with nonrespondents, suggested that 74% of HAN members were connected through mentorship ties and that all 97 members were connected through at least one form of collaboration. Mentorship and collaboration ties were present both within and across boundaries of HAN member organizations. SNA of public health collaborative networks provides understanding about the structure of relationships that are formed as a result of participation in network activities. This approach may offer members and funders a way to assess the impact of such networks that goes beyond simply measuring products and participation at the individual level.

  3. PA activity by using nuclear power plant safety demonstration and analysis

    International Nuclear Information System (INIS)

    Tsuchiya, Mitsuo; Kamimae, Rie

    1999-01-01

    INS/NUPEC presents one of Public acceptance (PA) methods for nuclear power in Japan, 'PA activity by using Nuclear Power Plant Safety Demonstration and Analysis', by using one of videos which is explained and analyzed accident events (Loss of Coolant Accident). Safety regulations of The National Government are strictly implemented in licensing at each of basic design and detailed design. To support safety regulation activities conducted by the National Government, INS/NLTPEC continuously implement Safety demonstration and analysis. With safety demonstration and analysis, made by assuming some abnormal conditions, what impacts could be produced by the assumed conditions are forecast based on specific design data on a given nuclear power plants. When analysis results compared with relevant decision criteria, the safety of nuclear power plants is confirmed. The decision criteria are designed to help judge if or not safety design of nuclear power plants is properly made. The decision criteria are set in the safety examination guidelines by taking sufficient safety allowance based on the latest technical knowledge obtained from a wide range of tests and safety studies. Safety demonstration and analysis is made by taking the procedure which are summarized in this presentation. In Japan, various PA (Public Acceptance) pamphlets and videos on nuclear energy have been published. But many of them focused on such topics as necessity or importance of nuclear energy, basic principles of nuclear power generation, etc., and a few described safety evaluation particularly of abnormal and accident events in accordance with the regulatory requirements. In this background, INS/NUPEC has been making efforts to prepare PA pamphlets and videos to explain the safety of nuclear power plants, to be simple and concrete enough, using various analytical computations for abnormal and accident events. In results, PA activity of INS/NUPEC is evaluated highly by the people

  4. Network Performance and Coordination in the Health, Education, Telecommunications System. Satellite Technology Demonstration, Technical Report No. 0422.

    Science.gov (United States)

    Braunstein, Jean; Janky, James M.

    This paper describes the network coordination for the Health, Education, Telecommunications (HET) system. Specifically, it discusses HET network performance as a function of a specially-developed coordination system which was designed to link terrestrial equipment to satellite operations centers. Because all procedures and equipment developed for…

  5. Investigation and analysis of network psychology of college students

    Institute of Scientific and Technical Information of China (English)

    Zhang Xiaoyan

    2013-01-01

    Based on basic situational research and analysis carried out on 638 college students using network,we found that as many as 20 percent of the students are not only largely dependent on internet,but also addicted to it.Further biography characteristics analyses for different individuals on the four dimensions of the network forced addiction,tolerance,and time management and interpersonal relationship and health,show that there are significant differences in grades,gender with different education levels of their parents.Further researches on discrepancy that addicted groups have in network entertainment addiction,network information,cyber porn,network relations and network transactions addictions also illustrate that significant discrepancies exist in gender,net age,different discipline and other factors.Finally we put forward some correlative measures to solve the problems of college students network psychology from individuals,schools,and society levels.

  6. Perturbation analysis of complete synchronization in networks of phase oscillators.

    Science.gov (United States)

    Tönjes, Ralf; Blasius, Bernd

    2009-08-01

    The behavior of weakly coupled self-sustained oscillators can often be well described by phase equations. Here we use the paradigm of Kuramoto phase oscillators which are coupled in a network to calculate first- and second-order corrections to the frequency of the fully synchronized state for nonidentical oscillators. The topology of the underlying coupling network is reflected in the eigenvalues and eigenvectors of the network Laplacian which influence the synchronization frequency in a particular way. They characterize the importance of nodes in a network and the relations between them. Expected values for the synchronization frequency are obtained for oscillators with quenched random frequencies on a class of scale-free random networks and for a Erdös-Rényi random network. We briefly discuss an application of the perturbation theory in the second order to network structural analysis.

  7. Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yunpeng Wang

    2014-01-01

    Full Text Available We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.

  8. Network externalities in telecommunication industry: An analysis of Serbian market

    Directory of Open Access Journals (Sweden)

    Trifunović Dejan

    2016-01-01

    Full Text Available This paper deals with network competition and provides empirical analysis of market concentration, network and call externalities, access pricing, price discrimination and switching costs in Serbian mobile phone telecommunications market. It is shown that network externalities governed the expansion of this market until 2008. Upon entry of VIP incumbents didn't engage in predatory behaviour towards entrant aiming to benefit from locked- in users. The policy of mobile phone number portability reduced on-net prices and substantially increased consumer's surplus. In contrast to some previous research, this policy was pro-competitive in Serbia. We have also determined that users of the network with the largest market share benefit the most from call externalities. Finally, one network does not price discriminate between outgoing and incoming roaming calls, which implies that users of this network have higher level pecuniary externalities in roaming compared to users of price discriminating networks.

  9. Incremental Centrality Algorithms for Dynamic Network Analysis

    Science.gov (United States)

    2013-08-01

    literature.   7.1.3 Small World Networks In 1998, Watts and Strogatz introduced a model that starts with a regular lattice (ring) of n nodes and...and S. Strogatz , "Collective Dynamics of ‘Small-World’ Networks," Nature, vol. 393, pp. 440-442, 1998. [13] T. Opsahl, "Structure and Evolution of...34On Random Graphs," Publicationes Mathematicae, vol. 6, 1959. [167] D.J. Watts and S.H. Strogatz , "Collective Dynamics of ‘Small-World’ Networks

  10. Fractal Analysis of Mobile Social Networks

    International Nuclear Information System (INIS)

    Zheng Wei; Pan Qian; Sun Chen; Deng Yu-Fan; Zhao Xiao-Kang; Kang Zhao

    2016-01-01

    Fractal and self similarity of complex networks have attracted much attention in recent years. The fractal dimension is a useful method to describe the fractal property of networks. However, the fractal features of mobile social networks (MSNs) are inadequately investigated. In this work, a box-covering method based on the ratio of excluded mass to closeness centrality is presented to investigate the fractal feature of MSNs. Using this method, we find that some MSNs are fractal at different time intervals. Our simulation results indicate that the proposed method is available for analyzing the fractal property of MSNs. (paper)

  11. Experimental demonstration of bandwidth on demand (BoD) provisioning based on time scheduling in software-defined multi-domain optical networks

    Science.gov (United States)

    Zhao, Yongli; Li, Yajie; Wang, Xinbo; Chen, Bowen; Zhang, Jie

    2016-09-01

    A hierarchical software-defined networking (SDN) control architecture is designed for multi-domain optical networks with the Open Daylight (ODL) controller. The OpenFlow-based Control Virtual Network Interface (CVNI) protocol is deployed between the network orchestrator and the domain controllers. Then, a dynamic bandwidth on demand (BoD) provisioning solution is proposed based on time scheduling in software-defined multi-domain optical networks (SD-MDON). Shared Risk Link Groups (SRLG)-disjoint routing schemes are adopted to separate each tenant for reliability. The SD-MDON testbed is built based on the proposed hierarchical control architecture. Then the proposed time scheduling-based BoD (Ts-BoD) solution is experimentally demonstrated on the testbed. The performance of the Ts-BoD solution is evaluated with respect to blocking probability, resource utilization, and lightpath setup latency.

  12. Global robust exponential stability analysis for interval recurrent neural networks

    International Nuclear Information System (INIS)

    Xu Shengyuan; Lam, James; Ho, Daniel W.C.; Zou Yun

    2004-01-01

    This Letter investigates the problem of robust global exponential stability analysis for interval recurrent neural networks (RNNs) via the linear matrix inequality (LMI) approach. The values of the time-invariant uncertain parameters are assumed to be bounded within given compact sets. An improved condition for the existence of a unique equilibrium point and its global exponential stability of RNNs with known parameters is proposed. Based on this, a sufficient condition for the global robust exponential stability for interval RNNs is obtained. Both of the conditions are expressed in terms of LMIs, which can be checked easily by various recently developed convex optimization algorithms. Examples are provided to demonstrate the reduced conservatism of the proposed exponential stability condition

  13. NAP: The Network Analysis Profiler, a web tool for easier topological analysis and comparison of medium-scale biological networks.

    Science.gov (United States)

    Theodosiou, Theodosios; Efstathiou, Georgios; Papanikolaou, Nikolas; Kyrpides, Nikos C; Bagos, Pantelis G; Iliopoulos, Ioannis; Pavlopoulos, Georgios A

    2017-07-14

    Nowadays, due to the technological advances of high-throughput techniques, Systems Biology has seen a tremendous growth of data generation. With network analysis, looking at biological systems at a higher level in order to better understand a system, its topology and the relationships between its components is of a great importance. Gene expression, signal transduction, protein/chemical interactions, biomedical literature co-occurrences, are few of the examples captured in biological network representations where nodes represent certain bioentities and edges represent the connections between them. Today, many tools for network visualization and analysis are available. Nevertheless, most of them are standalone applications that often (i) burden users with computing and calculation time depending on the network's size and (ii) focus on handling, editing and exploring a network interactively. While such functionality is of great importance, limited efforts have been made towards the comparison of the topological analysis of multiple networks. Network Analysis Provider (NAP) is a comprehensive web tool to automate network profiling and intra/inter-network topology comparison. It is designed to bridge the gap between network analysis, statistics, graph theory and partially visualization in a user-friendly way. It is freely available and aims to become a very appealing tool for the broader community. It hosts a great plethora of topological analysis methods such as node and edge rankings. Few of its powerful characteristics are: its ability to enable easy profile comparisons across multiple networks, find their intersection and provide users with simplified, high quality plots of any of the offered topological characteristics against any other within the same network. It is written in R and Shiny, it is based on the igraph library and it is able to handle medium-scale weighted/unweighted, directed/undirected and bipartite graphs. NAP is available at http://bioinformatics.med.uoc.gr/NAP .

  14. An artificial neural network approach to laser-induced breakdown spectroscopy quantitative analysis

    International Nuclear Information System (INIS)

    D’Andrea, Eleonora; Pagnotta, Stefano; Grifoni, Emanuela; Lorenzetti, Giulia; Legnaioli, Stefano; Palleschi, Vincenzo; Lazzerini, Beatrice

    2014-01-01

    The usual approach to laser-induced breakdown spectroscopy (LIBS) quantitative analysis is based on the use of calibration curves, suitably built using appropriate reference standards. More recently, statistical methods relying on the principles of artificial neural networks (ANN) are increasingly used. However, ANN analysis is often used as a ‘black box’ system and the peculiarities of the LIBS spectra are not exploited fully. An a priori exploration of the raw data contained in the LIBS spectra, carried out by a neural network to learn what are the significant areas of the spectrum to be used for a subsequent neural network delegated to the calibration, is able to throw light upon important information initially unknown, although already contained within the spectrum. This communication will demonstrate that an approach based on neural networks specially taylored for dealing with LIBS spectra would provide a viable, fast and robust method for LIBS quantitative analysis. This would allow the use of a relatively limited number of reference samples for the training of the network, with respect to the current approaches, and provide a fully automatizable approach for the analysis of a large number of samples. - Highlights: • A methodological approach to neural network analysis of LIBS spectra is proposed. • The architecture of the network and the number of inputs are optimized. • The method is tested on bronze samples already analyzed using a calibration-free LIBS approach. • The results are validated, compared and discussed

  15. Supplement analysis 2 of environmental impacts resulting from modifications in the West Valley Demonstration Project

    International Nuclear Information System (INIS)

    1998-01-01

    The West Valley Demonstration Project, located in western New York, has approximately 600,000 gallons of liquid high-level radioactive waste (HLW) in storage in underground tanks. While corrosion analysis has revealed that only limited tank degradation has taken place, the failure of these tanks could release HLW to the environment. Congress requires DOE to demonstrate the technology for removal and solidification of HLW. DOE issued the Final Environmental Impact Statement (FEIS) in 1982. The purpose of this second supplement analysis is to re-assess the 1982 Final Environmental Impact Statement's continued adequacy. This report provides the necessary and appropriate data for DOE to determine whether the environmental impacts presented by the ongoing refinements in the design, process, and operations of the Project are considered sufficiently bounded within the envelope of impacts presented in the FEIS and supporting documentation

  16. Bandwidth Analysis of Smart Meter Network Infrastructure

    DEFF Research Database (Denmark)

    Balachandran, Kardi; Olsen, Rasmus Løvenstein; Pedersen, Jens Myrup

    2014-01-01

    Advanced Metering Infrastructure (AMI) is a net-work infrastructure in Smart Grid, which links the electricity customers to the utility company. This network enables smart services by making it possible for the utility company to get an overview of their customers power consumption and also control...... devices in their costumers household e.g. heat pumps. With these smart services, utility companies can do load balancing on the grid by shifting load using resources the customers have. The problem investigated in this paper is what bandwidth require-ments can be expected when implementing such network...... to utilize smart meters and which existing broadband network technologies can facilitate this smart meter service. Initially, scenarios for smart meter infrastructure are identified. The paper defines abstraction models which cover the AMI scenarios. When the scenario has been identified a general overview...

  17. Stability analysis of impulsive parabolic complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Wang Jinliang, E-mail: wangjinliang1984@yahoo.com.cn [Science and Technology on Aircraft Control Laboratory, School of Automation Science and Electrical Engineering, Beihang University, XueYuan Road, No. 37, HaiDian District, Beijing 100191 (China); Wu Huaining [Science and Technology on Aircraft Control Laboratory, School of Automation Science and Electrical Engineering, Beihang University, XueYuan Road, No. 37, HaiDian District, Beijing 100191 (China)

    2011-11-15

    Highlights: > Two impulsive parabolic complex network models are proposed. > The global exponential stability of impulsive parabolic complex networks are considered. > The robust global exponential stability of impulsive parabolic complex networks are considered. - Abstract: In the present paper, two kinds of impulsive parabolic complex networks (IPCNs) are considered. In the first one, all nodes have the same time-varying delay. In the second one, different nodes have different time-varying delays. Using the Lyapunov functional method combined with the inequality techniques, some global exponential stability criteria are derived for the IPCNs. Furthermore, several robust global exponential stability conditions are proposed to take uncertainties in the parameters of the IPCNs into account. Finally, numerical simulations are presented to illustrate the effectiveness of the results obtained here.

  18. Transcription regulatory networks analysis using CAGE

    KAUST Repository

    Tegnér, Jesper N.

    2009-10-01

    Mapping out cellular networks in general and transcriptional networks in particular has proved to be a bottle-neck hampering our understanding of biological processes. Integrative approaches fusing computational and experimental technologies for decoding transcriptional networks at a high level of resolution is therefore of uttermost importance. Yet, this is challenging since the control of gene expression in eukaryotes is a complex multi-level process influenced by several epigenetic factors and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical interactions and computational prediction of regulatory motifs, which together can provide a genome-wide picture of eukaryotic transcriptional regulatory networks at a new level of resolution. © 2010 by Pan Stanford Publishing Pte. Ltd. All rights reserved.

  19. Stability analysis of impulsive parabolic complex networks

    International Nuclear Information System (INIS)

    Wang Jinliang; Wu Huaining

    2011-01-01

    Highlights: → Two impulsive parabolic complex network models are proposed. → The global exponential stability of impulsive parabolic complex networks are considered. → The robust global exponential stability of impulsive parabolic complex networks are considered. - Abstract: In the present paper, two kinds of impulsive parabolic complex networks (IPCNs) are considered. In the first one, all nodes have the same time-varying delay. In the second one, different nodes have different time-varying delays. Using the Lyapunov functional method combined with the inequality techniques, some global exponential stability criteria are derived for the IPCNs. Furthermore, several robust global exponential stability conditions are proposed to take uncertainties in the parameters of the IPCNs into account. Finally, numerical simulations are presented to illustrate the effectiveness of the results obtained here.

  20. Latent Space Approaches to Social Network Analysis

    National Research Council Canada - National Science Library

    Hoff, Peter D; Raftery, Adrian E; Handcock, Mark S

    2001-01-01

    .... In studies of social networks, recent emphasis has been placed on random graph models where the nodes usually represent individual social actors and the edges represent the presence of a specified...

  1. Social network analysis of sustainable transportation organizations.

    Science.gov (United States)

    2012-07-15

    Studying how organizations communicate with each other can provide important insights into the influence, and policy success of different types of organizations. This study examines the communication networks of 121 organizations promoting sustainabl...

  2. Network Analysis in Community Psychology: Looking Back, Looking Forward.

    Science.gov (United States)

    Neal, Zachary P; Neal, Jennifer Watling

    2017-09-01

    Network analysis holds promise for community psychology given the field's aim to understand the interplay between individuals and their social contexts. Indeed, because network analysis focuses explicitly on patterns of relationships between actors, its theories and methods are inherently extra-individual in nature and particularly well suited to characterizing social contexts. But, to what extent has community psychology taken advantage of this network analysis as a tool for capturing context? To answer these questions, this study provides a review of the use network analysis in articles published in American Journal of Community Psychology. Looking back, we describe and summarize the ways that network analysis has been employed in community psychology research to understand the range of ways community psychologists have found the technique helpful. Looking forward and paying particular attention to analytic issues identified in past applications, we provide some recommendations drawn from the network analysis literature to facilitate future applications of network analysis in community psychology. © 2017 The Authors. American Journal of Community Psychology published by Wiley Periodicals, Inc. on behalf of Society for Community Research and Action.

  3. Value Systems Alignment Analysis in Collaborative Networked Organizations Management

    OpenAIRE

    Patricia Macedo; Luis Camarinha-Matos

    2017-01-01

    The assessment of value systems alignment can play an important role in the formation and evolution of collaborative networks, contributing to reduce potential risks of collaboration. For this purpose, an assessment tool is proposed as part of a collaborative networks information system, supporting both the formation and evolution of long-term strategic alliances and goal-oriented networks. An implementation approach for value system alignment analysis is described, which is intended to assis...

  4. A cyberciege traffic analysis extension for teaching network security

    OpenAIRE

    Chang, Xuquan Stanley.; Chua, Kim Yong.

    2011-01-01

    CyberCIEGE is an interactive game simulating realistic scenarios that teaches the players Information Assurance (IA) concepts. The existing game scenarios only provide a high-level abstraction of the networked environment, e.g., nodes do not have Internet protocol (IP) addresses or belong to proper subnets, and there is no packet-level network simulation. This research explored endowing the game with network level traffic analysis, and implementing a game scenario to take advantage of this ne...

  5. Statistical and machine learning approaches for network analysis

    CERN Document Server

    Dehmer, Matthias

    2012-01-01

    Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation

  6. Analysis and Comparison of Typical Models within Distribution Network Design

    DEFF Research Database (Denmark)

    Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.

    This paper investigates the characteristics of typical optimisation models within Distribution Network Design. During the paper fourteen models known from the literature will be thoroughly analysed. Through this analysis a schematic approach to categorisation of distribution network design models...... for educational purposes. Furthermore, the paper can be seen as a practical introduction to network design modelling as well as a being an art manual or recipe when constructing such a model....

  7. Network similarity and statistical analysis of earthquake seismic data

    OpenAIRE

    Deyasi, Krishanu; Chakraborty, Abhijit; Banerjee, Anirban

    2016-01-01

    We study the structural similarity of earthquake networks constructed from seismic catalogs of different geographical regions. A hierarchical clustering of underlying undirected earthquake networks is shown using Jensen-Shannon divergence in graph spectra. The directed nature of links indicates that each earthquake network is strongly connected, which motivates us to study the directed version statistically. Our statistical analysis of each earthquake region identifies the hub regions. We cal...

  8. Performance demonstration program plan for RCRA constituent analysis of solidified wastes

    International Nuclear Information System (INIS)

    1995-06-01

    Performance Demonstration Programs (PDPS) are designed to help ensure compliance with the Quality Assurance Objectives (QAOs) for the Waste Isolation Pilot Plant (WIPP). The PDPs are intended for use by the Department of Energy (DOE) Carlsbad Area Office (CAO) to assess and approve the laboratories and other measurement facilities supplying services for the characterization of WIPP TRU waste. The PDPs may also be used by CAO in qualifying laboratories proposing to supply additional analytical services that are required for other than waste characterization, such as WIPP site operations. The purpose of this PDP is to test laboratory performance for the analysis of solidified waste samples for TRU waste characterization. This performance will be demonstrated by the successful analysis of blind audit samples of simulated, solidified TRU waste according to the criteria established in this plan. Blind audit samples (hereinafter referred to as PDP samples) will be used as an independent means to assess laboratory performance regarding compliance with the QAOs. The concentration of analytes in the PDP samples will address levels of regulatory concern and will encompass the range of concentrations anticipated in actual waste characterization samples. Analyses that are required by the WIPP to demonstrate compliance with various regulatory requirements and which are included in the PDP must be performed by laboratories that demonstrate acceptable performance in the PDP. These analyses are referred to as WIPP analyses and the samples on which they are performed are referred to as WIPP samples for the balance of this document

  9. Network analysis of Chinese provincial economies

    Science.gov (United States)

    Sun, Xiaoqi; An, Haizhong; Liu, Xiaojia

    2018-02-01

    Global economic system is a huge network formed by national subnetworks that contains the provincial networks. As the second largest world economy, China has "too big to fail" impact on the interconnected global economy. Detecting the critical sectors and vital linkages inside Chinese economic network is meaningful for understanding the origin of this Chinese impact. Different from tradition network research at national level, this paper focuses on the provincial networks and inter-provincial network. Using Chinese inter-regional input-output table to construct 30 provincial input-output networks and one inter-provincial input-output network, we identify central sectors and vital linkages, as well as analyze economic structure similarity. Results show that (1) Communication Devices sector in Guangdong and that in Jiangsu, Transportation and Storage sector in Shanghai play critical roles in Chinese economy. (2) Advanced manufactures and services industry occupy the central positions in eastern provincial economies, while Construction sector, Heavy industry, and Wholesale and Retail Trades sector are influential in middle and western provinces. (3) The critical monetary flow paths in Chinese economy are Communication Devices sector to Communication Devices sector in Guangdong, Metals Mining sector to Iron and Steel Smelting sector in Henan, Communication Devices sector to Communication Devices sector in Jiangsu, as well as Petroleum Mining sector in Heilongjiang to Petroleum Processing sector in Liaoning. (4) Collective influence results suggest that Finance sector, Transportation and Storage sector, Production of Electricity and Heat sector, and Rubber and Plastics sector in Hainan are strategic influencers, despite being weakly connected. These sectors and input-output relations are worthy of close attention for monitoring Chinese economy.

  10. Stochastic modeling and analysis of telecoms networks

    CERN Document Server

    Decreusefond, Laurent

    2012-01-01

    This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

  11. Analysis and Design of Complex Network Environments

    Science.gov (United States)

    2012-03-01

    and J. Lowe, “The myths and facts behind cyber security risks for industrial control systems ,” in the Proceedings of the VDE Kongress, VDE Congress...questions about 1) how to model them, 2) the design of experiments necessary to discover their structure (and thus adapt system inputs to optimize the...theoretical work that clarifies fundamental limitations of complex networks with network engineering and systems biology to implement specific designs and

  12. Conversation Analysis on Social Networking Sites

    OpenAIRE

    Belkaroui , Rami; Faiz , Rim; Elkhlifi , Aymen

    2014-01-01

    International audience; With the explosion of Web 2.0, people are becoming more communicative through expansion of services and multi-platform applications such as microblogs, forums and social networks which establishes social and collabora-tive backgrounds. These services can be seen as very large information repository containing millions of text messages usually organized into complex networks involving users interacting with each other at specific times. Several works focused only to ret...

  13. Social Network Analysis as a Methodological Approach to Explore Health Systems: A Case Study Exploring Support among Senior Managers/Executives in a Hospital Network.

    Science.gov (United States)

    De Brún, Aoife; McAuliffe, Eilish

    2018-03-13

    Health systems research recognizes the complexity of healthcare, and the interacting and interdependent nature of components of a health system. To better understand such systems, innovative methods are required to depict and analyze their structures. This paper describes social network analysis as a methodology to depict, diagnose, and evaluate health systems and networks therein. Social network analysis is a set of techniques to map, measure, and analyze social relationships between people, teams, and organizations. Through use of a case study exploring support relationships among senior managers in a newly established hospital group, this paper illustrates some of the commonly used network- and node-level metrics in social network analysis, and demonstrates the value of these maps and metrics to understand systems. Network analysis offers a valuable approach to health systems and services researchers as it offers a means to depict activity relevant to network questions of interest, to identify opinion leaders, influencers, clusters in the network, and those individuals serving as bridgers across clusters. The strengths and limitations inherent in the method are discussed, and the applications of social network analysis in health services research are explored.

  14. Social Network Analysis as a Methodological Approach to Explore Health Systems: A Case Study Exploring Support among Senior Managers/Executives in a Hospital Network

    Directory of Open Access Journals (Sweden)

    Aoife De Brún

    2018-03-01

    Full Text Available Health systems research recognizes the complexity of healthcare, and the interacting and interdependent nature of components of a health system. To better understand such systems, innovative methods are required to depict and analyze their structures. This paper describes social network analysis as a methodology to depict, diagnose, and evaluate health systems and networks therein. Social network analysis is a set of techniques to map, measure, and analyze social relationships between people, teams, and organizations. Through use of a case study exploring support relationships among senior managers in a newly established hospital group, this paper illustrates some of the commonly used network- and node-level metrics in social network analysis, and demonstrates the value of these maps and metrics to understand systems. Network analysis offers a valuable approach to health systems and services researchers as it offers a means to depict activity relevant to network questions of interest, to identify opinion leaders, influencers, clusters in the network, and those individuals serving as bridgers across clusters. The strengths and limitations inherent in the method are discussed, and the applications of social network analysis in health services research are explored.

  15. Empirical analysis of online social networks in the age of Web 2.0

    Science.gov (United States)

    Fu, Feng; Liu, Lianghuan; Wang, Long

    2008-01-01

    Today the World Wide Web is undergoing a subtle but profound shift to Web 2.0, to become more of a social web. The use of collaborative technologies such as blogs and social networking site (SNS) leads to instant online community in which people communicate rapidly and conveniently with each other. Moreover, there are growing interest and concern regarding the topological structure of these new online social networks. In this paper, we present empirical analysis of statistical properties of two important Chinese online social networks-a blogging network and an SNS open to college students. They are both emerging in the age of Web 2.0. We demonstrate that both networks possess small-world and scale-free features already observed in real-world and artificial networks. In addition, we investigate the distribution of topological distance. Furthermore, we study the correlations between degree (in/out) and degree (in/out), clustering coefficient and degree, popularity (in terms of number of page views) and in-degree (for the blogging network), respectively. We find that the blogging network shows disassortative mixing pattern, whereas the SNS network is an assortative one. Our research may help us to elucidate the self-organizing structural characteristics of these online social networks embedded in technical forms.

  16. Towards the integration of social network analysis in an inter-organizational networks perspective

    DEFF Research Database (Denmark)

    Bergenholtz, Carsten; Waldstrøm, Christian

    This conceptual paper deals with the issue of studying inter-organizational networks while applying social network analysis (SNA). SNA is a widely recognized technique in network research, particularly within intra-organizational settings, while there seems to be a significant gap in the inter......-organizational setting. Based on a literature review of both SNA as a methodology and/or theory and the field of inter-organizational networks, the aim is to gain an overview in order to provide a clear setting for SNA in inter-organizational research....

  17. Data analysis on work activities in dismantling of Japan Power Demonstration Reactor (JPDR). Contract research

    International Nuclear Information System (INIS)

    Shiraishi, Kunio; Sukegawa, Takenori; Yanagihara, Satoshi

    1998-03-01

    The safe dismantling of a retired nuclear power plant was demonstrated by completion of dismantling activities for the Japan Power Demonstration Reactor (JPDR), March, 1996, which had been conducted since 1986. This project was a flag ship project for dismantling of nuclear power plants in Japan, aiming at demonstrating an applicability of developed dismantling techniques in actual dismantling work, developing database on work activities as well as dismantling of components and structures. Various data on dismantling activities were therefore systematically collected and these were accumulated on computer files to build the decommissioning database; dismantling activities were characterized by analyzing the data. The data analysis resulted in producing general forms such as unit activity factors, for example, manpower need per unit weight of component to be dismantled, and simple arithmetic forms for forecasting of project management data to be applied to planning another dismantling project through the evaluation for general use of the analyzed data. The results of data analysis could be usefully applied to planning of future decommissioning of commercial nuclear power plants in Japan. This report describes the data collection and analysis on the JPDR dismantling activities. (author)

  18. Using network analysis to study behavioural phenotypes: an example using domestic dogs.

    Science.gov (United States)

    Goold, Conor; Vas, Judit; Olsen, Christine; Newberry, Ruth C

    2016-10-01

    Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs ( Canis lupus familiaris ). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with 'Playful' being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.

  19. Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

    Science.gov (United States)

    Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

    2013-12-01

    Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

  20. Assessing Group Interaction with Social Language Network Analysis

    Science.gov (United States)

    Scholand, Andrew J.; Tausczik, Yla R.; Pennebaker, James W.

    In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

  1. [Social network analysis of interdisciplinary cooperation and networking in early prevention and intervention. A pilot study].

    Science.gov (United States)

    Künster, A K; Knorr, C; Fegert, J M; Ziegenhain, U

    2010-11-01

    Child protection can only be successfully solved by interdisciplinary cooperation and networking. The individual, heterogeneous, and complex needs of families cannot be met sufficiently by one profession alone. To guarantee efficient interdisciplinary cooperation, there should not be any gaps in the network. In addition, each actor in the network should be placed at an optimal position regarding function, responsibilities, and skills. Actors that serve as allocators, such as pediatricians or youth welfare officers, should be in key player positions within the network. Furthermore, successful child protection is preventive and starts early. Social network analysis is an adequate technique to assess network structures and to plan interventions to improve networking. In addition, it is very useful to evaluate the effectiveness of interventions like round tables. We present data from our pilot project which was part of "Guter Start ins Kinderleben" ("a good start into a child's life"). Exemplary network data from one community show that networking is already quite effective with a satisfactory mean density throughout the network. There is potential for improvement in cooperation, especially at the interface between the child welfare and health systems.

  2. Efficient computation of aerodynamic influence coefficients for aeroelastic analysis on a transputer network

    Science.gov (United States)

    Janetzke, David C.; Murthy, Durbha V.

    1991-01-01

    Aeroelastic analysis is multi-disciplinary and computationally expensive. Hence, it can greatly benefit from parallel processing. As part of an effort to develop an aeroelastic capability on a distributed memory transputer network, a parallel algorithm for the computation of aerodynamic influence coefficients is implemented on a network of 32 transputers. The aerodynamic influence coefficients are calculated using a 3-D unsteady aerodynamic model and a parallel discretization. Efficiencies up to 85 percent were demonstrated using 32 processors. The effect of subtask ordering, problem size, and network topology are presented. A comparison to results on a shared memory computer indicates that higher speedup is achieved on the distributed memory system.

  3. Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling.

    Directory of Open Access Journals (Sweden)

    Junha Shin

    Full Text Available Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life-Archaea, Bacteria, and Eukaryota-suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co

  4. SNAPS : semantic network traffic analysis through projection and selection

    NARCIS (Netherlands)

    Cappers, B.C.M.; van Wijk, J.J.; Harrison, L.; Prigent, N.; Engle, S.; Best, D.; Goodall, J.

    2015-01-01

    Most network traffic analysis applications are designed to discover malicious activity by only relying on high-level flow-based message properties. However, to detect security breaches that are specifically designed to target one network (e.g., Advanced Persistent Threats), deep packet inspection

  5. An Analysis of the Structure and Evolution of Networks

    Science.gov (United States)

    Hua, Guangying

    2011-01-01

    As network research receives more and more attention from both academic researchers and practitioners, network analysis has become a fast growing field attracting many researchers from diverse fields such as physics, computer science, and sociology. This dissertation provides a review of theory and research on different real data sets from the…

  6. Transient stability analysis of a distribution network with distributed generators

    NARCIS (Netherlands)

    Xyngi, I.; Ishchenko, A.; Popov, M.; Sluis, van der L.

    2009-01-01

    This letter describes the transient stability analysis of a 10-kV distribution network with wind generators, microturbines, and CHP plants. The network being modeled in Matlab/Simulink takes into account detailed dynamic models of the generators. Fault simulations at various locations are

  7. Network analysis reveals multiscale controls on streamwater chemistry

    Science.gov (United States)

    Kevin J. McGuire; Christian E. Torgersen; Gene E. Likens; Donald C. Buso; Winsor H. Lowe; Scott W. Bailey

    2014-01-01

    By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in...

  8. Safety analysis report for packaging (onsite) transuranic performance demonstration program sample packaging

    International Nuclear Information System (INIS)

    Mccoy, J.C.

    1997-01-01

    The Transuranic Performance Demonstration Program (TPDP) sample packaging is used to transport highway route controlled quantities of weapons grade (WG) plutonium samples from the Plutonium Finishing Plant (PFP) to the Waste Receiving and Processing (WRAP) facility and back. The purpose of these shipments is to test the nondestructive assay equipment in the WRAP facility as part of the Nondestructive Waste Assay PDP. The PDP is part of the U. S. Department of Energy (DOE) National TRU Program managed by the U. S. Department of Energy, Carlsbad Area Office, Carlsbad, New Mexico. Details of this program are found in CAO-94-1045, Performance Demonstration Program Plan for Nondestructive Assay for the TRU Waste Characterization Program (CAO 1994); INEL-96/0129, Design of Benign Matrix Drums for the Non-Destructive Assay Performance Demonstration Program for the National TRU Program (INEL 1996a); and INEL-96/0245, Design of Phase 1 Radioactive Working Reference Materials for the Nondestructive Assay Performance Demonstration Program for the National TRU Program (INEL 1996b). Other program documentation is maintained by the national TRU program and each DOE site participating in the program. This safety analysis report for packaging (SARP) provides the analyses and evaluations necessary to demonstrate that the TRU PDP sample packaging meets the onsite transportation safety requirements of WHC-CM-2-14, Hazardous Material Packaging and Shipping, for an onsite Transportation Hazard Indicator (THI) 2 packaging. This SARP, however, does not include evaluation of any operations within the PFP or WRAP facilities, including handling, maintenance, storage, or operating requirements, except as they apply directly to transportation between the gate of PFP and the gate of the WRAP facility. All other activities are subject to the requirements of the facility safety analysis reports (FSAR) of the PFP or WRAP facility and requirements of the PDP

  9. Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets.

    Science.gov (United States)

    Mayo, Charles; Conners, Steve; Warren, Christopher; Miller, Robert; Court, Laurence; Popple, Richard

    2013-11-01

    With emergence of clinical outcomes databases as tools utilized routinely within institutions, comes need for software tools to support automated statistical analysis of these large data sets and intrainstitutional exchange from independent federated databases to support data pooling. In this paper, the authors present a design approach and analysis methodology that addresses both issues. A software application was constructed to automate analysis of patient outcomes data using a wide range of statistical metrics, by combining use of C#.Net and R code. The accuracy and speed of the code was evaluated using benchmark data sets. The approach provides data needed to evaluate combinations of statistical measurements for ability to identify patterns of interest in the data. Through application of the tools to a benchmark data set for dose-response threshold and to SBRT lung data sets, an algorithm was developed that uses receiver operator characteristic curves to identify a threshold value and combines use of contingency tables, Fisher exact tests, Welch t-tests, and Kolmogorov-Smirnov tests to filter the large data set to identify values demonstrating dose-response. Kullback-Leibler divergences were used to provide additional confirmation. The work demonstrates the viability of the design approach and the software tool for analysis of large data sets.

  10. Feasibility and demonstration of a cloud-based RIID analysis system

    Science.gov (United States)

    Wright, Michael C.; Hertz, Kristin L.; Johnson, William C.; Sword, Eric D.; Younkin, James R.; Sadler, Lorraine E.

    2015-06-01

    A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed.

  11. Analysis of the Chinese air route network as a complex network

    Science.gov (United States)

    Cai, Kai-Quan; Zhang, Jun; Du, Wen-Bo; Cao, Xian-Bin

    2012-02-01

    The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network (CARN) within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network (CAN). Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.

  12. PROJECT ACTIVITY ANALYSIS WITHOUT THE NETWORK MODEL

    Directory of Open Access Journals (Sweden)

    S. Munapo

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.

    AFRIKAANSE OPSOMMING: Die navorsing beskryf ’n nuwerwetse metode vir die ontleding en bestuur van die sekwensiële aktiwiteite van projekte. Die voorgestelde metode bepaal kritiese aktiwiteite, die kritieke pad, aanvangstye, speling, verhasing, en ander groothede sonder die gebruik van ’n netwerkmodel. Die metode funksioneer bevredigend in die praktyk, en omseil die administratiewe rompslomp van die tradisionele netwerkmodelle.

  13. Hierarchical analysis of dependency in metabolic networks.

    Science.gov (United States)

    Gagneur, Julien; Jackson, David B; Casari, Georg

    2003-05-22

    Elucidation of metabolic networks for an increasing number of organisms reveals that even small networks can contain thousands of reactions and chemical species. The intimate connectivity between components complicates their decomposition into biologically meaningful sub-networks. Moreover, traditional higher-order representations of metabolic networks as metabolic pathways, suffers from the lack of rigorous definition, yielding pathways of disparate content and size. We introduce a hierarchical representation that emphasizes the gross organization of metabolic networks in largely independent pathways and sub-systems at several levels of independence. The approach highlights the coupling of different pathways and the shared compounds responsible for those couplings. By assessing our results on Escherichia coli (E.coli metabolic reactions, Genetic Circuits Research Group, University of California, San Diego, http://gcrg.ucsd.edu/organisms/ecoli.html, 'model v 1.01. reactions') against accepted biochemical annotations, we provide the first systematic synopsis of an organism's metabolism. Comparison with operons of E.coli shows that low-level clusters are reflected in genome organization and gene regulation. Source code, data sets and supplementary information are available at http://www.mas.ecp.fr/labo/equipe/gagneur/hierarchy/hierarchy.html

  14. SBEToolbox: A Matlab Toolbox for Biological Network Analysis.

    Science.gov (United States)

    Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J

    2013-01-01

    We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases.

  15. Category theoretic analysis of hierarchical protein materials and social networks.

    Directory of Open Access Journals (Sweden)

    David I Spivak

    Full Text Available Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.

  16. Demonstration of risk-based decision analysis in remedial alternative selection and design

    International Nuclear Information System (INIS)

    Evans, E.K.; Duffield, G.M.; Massmann, J.W.; Freeze, R.A.; Stephenson, D.E.

    1993-01-01

    This study demonstrates the use of risk-based decision analysis (Massmann and Freeze 1987a, 1987b) in the selection and design of an engineering alternative for groundwater remediation at a waste site at the Savannah River Site, a US Department of Energy facility in South Carolina. The investigation focuses on the remediation and closure of the H-Area Seepage Basins, an inactive disposal site that formerly received effluent water from a nearby production facility. A previous study by Duffield et al. (1992), which used risk-based decision analysis to screen a number of ground-water remediation alternatives under consideration for this site, indicated that the most attractive remedial option is ground-water extraction by wells coupled with surface water discharge of treated effluent. The aim of the present study is to demonstrate the iterative use of risk-based decision analysis throughout the design of a particular remedial alternative. In this study, we consider the interaction between two episodes of aquifer testing over a 6-year period and the refinement of a remedial extraction well system design. Using a three-dimensional ground-water flow model, this study employs (1) geostatistics and Monte Carlo techniques to simulate hydraulic conductivity as a stochastic process and (2) Bayesian updating and conditional simulation to investigate multiple phases of aquifer testing. In our evaluation of a remedial alternative, we compute probabilistic costs associated with the failure of an alternative to completely capture a simulated contaminant plume. The results of this study demonstrate the utility of risk-based decision analysis as a tool for improving the design of a remedial alternative through the course of phased data collection at a remedial site

  17. Performance Analysis of IIUM Wireless Campus Network

    International Nuclear Information System (INIS)

    Latif, Suhaimi Abd; Masud, Mosharrof H; Anwar, Farhat

    2013-01-01

    International Islamic University Malaysia (IIUM) is one of the leading universities in the world in terms of quality of education that has been achieved due to providing numerous facilities including wireless services to every enrolled student. The quality of this wireless service is controlled and monitored by Information Technology Division (ITD), an ISO standardized organization under the university. This paper aims to investigate the constraints of wireless campus network of IIUM. It evaluates the performance of the IIUM wireless campus network in terms of delay, throughput and jitter. QualNet 5.2 simulator tool has employed to measure these performances of IIUM wireless campus network. The observation from the simulation result could be one of the influencing factors in improving wireless services for ITD and further improvement

  18. Multilayer Network Analysis of Nuclear Reactions

    Science.gov (United States)

    Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

    2016-08-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, 4He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart.

  19. Modelling, synthesis and analysis of biorefinery networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona

    for the conversion of biomass into chemicals, fuels and energy, because they have the potential to maximize biomass value while reducing emissions. The design of biorefinery networks is a complex decisionmaking problem that involves the selection of feedstocks, processing technologies, products, geographical...... locations, and operating conditions, among others. Unlike petroleumbased processing networks, biorefineries rely on feedstocks that are nonhomogeneous across geographical areas in terms of their availability, type and properties. For this reason, the performance of biorefinery networks depends...... of reactions to convert available biomassbased feedstocks into desired products, the selection of processing routes and technologies from a large set of alternatives, or the generation of hybrid technologies through process intensification. Systematic process synthesis and design methods have been developed...

  20. Analysis of remote synchronization in complex networks

    Science.gov (United States)

    Gambuzza, Lucia Valentina; Cardillo, Alessio; Fiasconaro, Alessandro; Fortuna, Luigi; Gómez-Gardeñes, Jesus; Frasca, Mattia

    2013-12-01

    A novel regime of synchronization, called remote synchronization, where the peripheral nodes form a phase synchronized cluster not including the hub, was recently observed in star motifs [Bergner et al., Phys. Rev. E 85, 026208 (2012)]. We show the existence of a more general dynamical state of remote synchronization in arbitrary networks of coupled oscillators. This state is characterized by the synchronization of pairs of nodes that are not directly connected via a physical link or any sequence of synchronized nodes. This phenomenon is almost negligible in networks of phase oscillators as its underlying mechanism is the modulation of the amplitude of those intermediary nodes between the remotely synchronized units. Our findings thus show the ubiquity and robustness of these states and bridge the gap from their recent observation in simple toy graphs to complex networks.

  1. Tank 241-AX-104 upper vadose zone cone penetrometer demonstration sampling and analysis plan

    International Nuclear Information System (INIS)

    FIELD, J.G.

    1999-01-01

    This sampling and analysis plan (SAP) is the primary document describing field and laboratory activities and requirements for the tank 241-AX-104 upper vadose zone cone penetrometer (CP) demonstration. It is written in accordance with Hanford Tank Initiative Tank 241-AX-104 Upper Vadose Zone Demonstration Data Quality Objective (Banning 1999). This technology demonstration, to be conducted at tank 241-AX-104, is being performed by the Hanford Tanks Initiative (HTI) Project as a part of Tank Waste Remediation System (TWRS) Retrieval Program (EM-30) and the Office of Science and Technology (EM-50) Tanks Focus Area. Sample results obtained as part of this demonstration will provide additional information for subsequent revisions to the Retrieval Performance Evaluation (RPE) report (Jacobs 1998). The RPE Report is the result of an evaluation of a single tank farm (AX Tank Farm) used as the basis for demonstrating a methodology for developing the data and analyses necessary to support making tank waste retrieval decisions within the context of tank farm closure requirements. The RPE includes a study of vadose zone contaminant transport mechanisms, including analysis of projected tank leak characteristics, hydrogeologic characteristics of tank farm soils, and the observed distribution of contaminants in the vadose zone in the tank farms. With limited characterization information available, large uncertainties exist as to the nature and extent of contaminants that may exist in the upper vadose zone in the AX Tank Farm. Traditionally, data has been collected from soils in the vadose zone through the installation of boreholes and wells. Soil samples are collected as the bore hole is advanced and samples are screened on site and/or sent to a laboratory for analysis. Some in-situ geophysical methods of contaminant analysis can be used to evaluate radionuclide levels in the soils adjacent to an existing borehole. However, geophysical methods require compensation for well

  2. A reliability analysis tool for SpaceWire network

    Science.gov (United States)

    Zhou, Qiang; Zhu, Longjiang; Fei, Haidong; Wang, Xingyou

    2017-04-01

    A SpaceWire is a standard for on-board satellite networks as the basis for future data-handling architectures. It is becoming more and more popular in space applications due to its technical advantages, including reliability, low power and fault protection, etc. High reliability is the vital issue for spacecraft. Therefore, it is very important to analyze and improve the reliability performance of the SpaceWire network. This paper deals with the problem of reliability modeling and analysis with SpaceWire network. According to the function division of distributed network, a reliability analysis method based on a task is proposed, the reliability analysis of every task can lead to the system reliability matrix, the reliability result of the network system can be deduced by integrating these entire reliability indexes in the matrix. With the method, we develop a reliability analysis tool for SpaceWire Network based on VC, where the computation schemes for reliability matrix and the multi-path-task reliability are also implemented. By using this tool, we analyze several cases on typical architectures. And the analytic results indicate that redundancy architecture has better reliability performance than basic one. In practical, the dual redundancy scheme has been adopted for some key unit, to improve the reliability index of the system or task. Finally, this reliability analysis tool will has a directive influence on both task division and topology selection in the phase of SpaceWire network system design.

  3. Analysis of Blocking Rate and Bandwidth Usage of Mobile IPTV Services in Wireless Cellular Networks

    Directory of Open Access Journals (Sweden)

    Mingfu Li

    2014-01-01

    Full Text Available Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  4. Analysis of blocking rate and bandwidth usage of mobile IPTV services in wireless cellular networks.

    Science.gov (United States)

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  5. Throughput Analysis of Large Wireless Networks with Regular Topologies

    Directory of Open Access Journals (Sweden)

    Hong Kezhu

    2007-01-01

    Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.

  6. Throughput Analysis of Large Wireless Networks with Regular Topologies

    Directory of Open Access Journals (Sweden)

    Kezhu Hong

    2007-04-01

    Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.

  7. An Approach to Data Analysis in 5G Networks

    Directory of Open Access Journals (Sweden)

    Lorena Isabel Barona López

    2017-02-01

    Full Text Available 5G networks expect to provide significant advances in network management compared to traditional mobile infrastructures by leveraging intelligence capabilities such as data analysis, prediction, pattern recognition and artificial intelligence. The key idea behind these actions is to facilitate the decision-making process in order to solve or mitigate common network problems in a dynamic and proactive way. In this context, this paper presents the design of Self-Organized Network Management in Virtualized and Software Defined Networks (SELFNET Analyzer Module, which main objective is to identify suspicious or unexpected situations based on metrics provided by different network components and sensors. The SELFNET Analyzer Module provides a modular architecture driven by use cases where analytic functions can be easily extended. This paper also proposes the data specification to define the data inputs to be taking into account in diagnosis process. This data specification has been implemented with different use cases within SELFNET Project, proving its effectiveness.

  8. Analysis of Privacy on Social Networks

    OpenAIRE

    Tomandl, Luboš

    2015-01-01

    This thesis deals with a question of privacy in a context of social networks. The main substance of these services is the users' option to share an information about their lives. This alone can be a problem for privacy. In the first part of this thesis concentrates on the meaning of privacy as well as its value for both individuals and the society. In the next part the privacy threats on social networks, namely Facebook, are discussed. These threats are disclosed on four levels according to f...

  9. Alpha spectral analysis via artificial neural networks

    International Nuclear Information System (INIS)

    Kangas, L.J.; Hashem, S.; Keller, P.E.; Kouzes, R.T.; Troyer, G.L.

    1994-10-01

    An artificial neural network system that assigns quality factors to alpha particle energy spectra is discussed. The alpha energy spectra are used to detect plutonium contamination in the work environment. The quality factors represent the levels of spectral degradation caused by miscalibration and foreign matter affecting the instruments. A set of spectra was labeled with a quality factor by an expert and used in training the artificial neural network expert system. The investigation shows that the expert knowledge of alpha spectra quality factors can be transferred to an ANN system

  10. Network graph analysis and visualization with Gephi

    CERN Document Server

    Cherven, Ken

    2013-01-01

    A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details.

  11. Geometrical methods for power network analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bellucci, Stefano; Tiwari, Bhupendra Nath [Istituto Nazioneale di Fisica Nucleare, Frascati, Rome (Italy). Lab. Nazionali di Frascati; Gupta, Neeraj [Indian Institute of Technology, Kanpur (India). Dept. of Electrical Engineering

    2013-02-01

    Uses advanced geometrical methods to analyse power networks. Provides a self-contained and tutorial introduction. Includes a fully worked-out example for the IEEE 5 bus system. This book is a short introduction to power system planning and operation using advanced geometrical methods. The approach is based on well-known insights and techniques developed in theoretical physics in the context of Riemannian manifolds. The proof of principle and robustness of this approach is examined in the context of the IEEE 5 bus system. This work addresses applied mathematicians, theoretical physicists and power engineers interested in novel mathematical approaches to power network theory.

  12. Satellite communications network design and analysis

    CERN Document Server

    Jo, Kenneth Y

    2011-01-01

    This authoritative book provides a thorough understanding of the fundamental concepts of satellite communications (SATCOM) network design and performance assessments. You find discussions on a wide class of SATCOM networks using satellites as core components, as well as coverage key applications in the field. This in-depth resource presents a broad range of critical topics, from geosynchronous Earth orbiting (GEO) satellites and direct broadcast satellite systems, to low Earth orbiting (LEO) satellites, radio standards and protocols.This invaluable reference explains the many specific uses of

  13. Social network analysis of public health programs to measure partnership.

    Science.gov (United States)

    Schoen, Martin W; Moreland-Russell, Sarah; Prewitt, Kim; Carothers, Bobbi J

    2014-12-01

    In order to prevent chronic diseases, community-based programs are encouraged to take an ecological approach to public health promotion and involve many diverse partners. Little is known about measuring partnership in implementing public health strategies. We collected data from 23 Missouri communities in early 2012 that received funding from three separate programs to prevent obesity and/or reduce tobacco use. While all of these funding programs encourage partnership, only the Social Innovation for Missouri (SIM) program included a focus on building community capacity and enhancing collaboration. Social network analysis techniques were used to understand contact and collaboration networks in community organizations. Measurements of average degree, density, degree centralization, and betweenness centralization were calculated for each network. Because of the various sizes of the networks, we conducted comparative analyses with and without adjustment for network size. SIM programs had increased measurements of average degree for partner collaboration and larger networks. When controlling for network size, SIM groups had higher measures of network density and lower measures of degree centralization and betweenness centralization. SIM collaboration networks were more dense and less centralized, indicating increased partnership. The methods described in this paper can be used to compare partnership in community networks of various sizes. Further research is necessary to define causal mechanisms of partnership development and their relationship to public health outcomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Error performance analysis in downlink cellular networks with interference management

    KAUST Repository

    Afify, Laila H.

    2015-05-01

    Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models have succeeded to account for the cellular network geometry, they mostly abstract many important wireless communication system aspects (e.g., modulation techniques, signal recovery techniques). Recently, a novel stochastic geometry model, based on the Equivalent-in-Distribution (EiD) approach, succeeded to capture the aforementioned communication system aspects and extend the analysis to averaged error performance, however, on the expense of increasing the modeling complexity. Inspired by the EiD approach, the analysis developed in [1] takes into consideration the key system parameters, while providing a simple tractable analysis. In this paper, we extend this framework to study the effect of different interference management techniques in downlink cellular network. The accuracy of the proposed analysis is verified via Monte Carlo simulations.

  15. Combining morphological analysis and Bayesian Networks for strategic decision support

    CSIR Research Space (South Africa)

    De Waal, AJ

    2007-12-01

    Full Text Available Morphological analysis (MA) and Bayesian networks (BN) are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating...

  16. C2 Network Analysis: Insights into Coordination & Understanding

    National Research Council Canada - National Science Library

    Hansberger, Jeffrey T; Schreiber, Craig; Spain, Randall D

    2008-01-01

    ...) workload management. This paper will address recent efforts, tools, and approaches on measuring and analyzing two of these distributed cognitive attributes through network analysis, coordination across agents and mental models...

  17. Flory-Stockmayer analysis on reprocessable polymer networks

    Science.gov (United States)

    Li, Lingqiao; Chen, Xi; Jin, Kailong; Torkelson, John

    Reprocessable polymer networks can undergo structure rearrangement through dynamic chemistries under proper conditions, making them a promising candidate for recyclable crosslinked materials, e.g. tires. This research field has been focusing on various chemistries. However, there has been lacking of an essential physical theory explaining the relationship between abundancy of dynamic linkages and reprocessability. Based on the classical Flory-Stockmayer analysis on network gelation, we developed a similar analysis on reprocessable polymer networks to quantitatively predict the critical condition for reprocessability. Our theory indicates that it is unnecessary for all bonds to be dynamic to make the resulting network reprocessable. As long as there is no percolated permanent network in the system, the material can fully rearrange. To experimentally validate our theory, we used a thiol-epoxy network model system with various dynamic linkage compositions. The stress relaxation behavior of resulting materials supports our theoretical prediction: only 50 % of linkages between crosslinks need to be dynamic for a tri-arm network to be reprocessable. Therefore, this analysis provides the first fundamental theoretical platform for designing and evaluating reprocessable polymer networks. We thank McCormick Research Catalyst Award Fund and ISEN cluster fellowship (L. L.) for funding support.

  18. Preliminary analysis of West Valley Waste Removal System equipment development and mock demonstration facilities

    International Nuclear Information System (INIS)

    Janicek, G.P.

    1981-06-01

    This report defines seven areas requiring further investigation to develop and demonstrate a safe and viable West Valley Waste Removal System. These areas of endeavor are discussed in terms of their minimum facility requirements. It is concluded that utilizing separated specific facilities at different points in time is of a greater advantage than an exact duplication of the West Valley tanks. Savannah River Plant's full-scale, full-circle and half-circle tanks, and their twelfth scale model tank would all be useful to varying degrees but would require modifications. Hanford's proposed full-size mock tank would be useful, but is not seriously considered because its construction may not coincide with West Valley needs. Costs of modifying existing facilities and/or constructing new facilities are assessed in terms of their benefit to the equipment development and mock demonstration. Six facilities were identified for further analysis which would benefit development of waste removal equipment

  19. Design, demonstration and analysis of a modified wavelength-correlating receiver for incoherent OCDMA system.

    Science.gov (United States)

    Zhou, Heng; Qiu, Kun; Wang, Leyang

    2011-03-28

    A novel wavelength-correlating receiver for incoherent Optical Code Division Multiple Access (OCDMA) system is proposed and demonstrated in this paper. Enabled by the wavelength conversion based scheme, the proposed receiver can support various code types including one-dimensional optical codes and time-spreading/wavelength-hopping two dimensional codes. Also, a synchronous detection scheme with time-to- wavelength based code acquisition is proposed, by which code acquisition time can be substantially reduced. Moreover, a novel data-validation methodology based on all-optical pulse-width monitoring is introduced for the wavelength-correlating receiver. Experimental demonstration of the new proposed receiver is presented and low bit error rate data-receiving is achieved without optical hard limiting and electronic power thresholding. For the first time, a detailed theoretical performance analysis specialized for the wavelength-correlating receiver is presented. Numerical results show that the overall performance of the proposed receiver prevails over conventional OCDMA receivers.

  20. Policy Analysis Screening System (PASS) demonstration: sample queries and terminal instructions

    Energy Technology Data Exchange (ETDEWEB)

    None

    1979-10-16

    This document contains the input and output for the Policy Analysis Screening System (PASS) demonstration. This demonstration is stored on a portable disk at the Environmental Impacts Division. Sample queries presented here include: (1) how to use PASS; (2) estimated 1995 energy consumption from Mid-Range Energy-Forecasting System (MEFS) data base; (3) pollution projections from Strategic Environmental Assessment System (SEAS) data base; (4) diesel auto regulations; (5) diesel auto health effects; (6) oil shale health and safety measures; (7) water pollution effects of SRC; (8) acid rainfall from Energy Environmental Statistics (EES) data base; 1990 EIA electric generation by fuel type; sulfate concentrations by Federal region; forecast of 1995 SO/sub 2/ emissions in Region III; and estimated electrical generating capacity in California to 1990. The file name for each query is included.

  1. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics.

    Science.gov (United States)

    Prescott, Aaron M; McCollough, Forest W; Eldreth, Bryan L; Binder, Brad M; Abel, Steven M

    2016-01-01

    Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. The dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i) whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii) what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB). In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB). Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations, and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms underlying ethylene

  2. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics

    Directory of Open Access Journals (Sweden)

    Aaron M. Prescott

    2016-08-01

    Full Text Available Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. However, the dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB. In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB. Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms

  3. Advanced reactor passive system reliability demonstration analysis for an external event

    International Nuclear Information System (INIS)

    Bucknor, Matthew; Grabaskas, David; Brunett, Acacia J.; Grelle, Austin

    2017-01-01

    Many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has been examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event

  4. Advanced Reactor Passive System Reliability Demonstration Analysis for an External Event

    Directory of Open Access Journals (Sweden)

    Matthew Bucknor

    2017-03-01

    Full Text Available Many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has been examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general for the postulated transient event.

  5. Advanced reactor passive system reliability demonstration analysis for an external event

    Energy Technology Data Exchange (ETDEWEB)

    Bucknor, Matthew; Grabaskas, David; Brunett, Acacia J.; Grelle, Austin [Argonne National Laboratory, Argonne (United States)

    2017-03-15

    Many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has been examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event.

  6. Value Systems Alignment Analysis in Collaborative Networked Organizations Management

    Directory of Open Access Journals (Sweden)

    Patricia Macedo

    2017-11-01

    Full Text Available The assessment of value systems alignment can play an important role in the formation and evolution of collaborative networks, contributing to reduce potential risks of collaboration. For this purpose, an assessment tool is proposed as part of a collaborative networks information system, supporting both the formation and evolution of long-term strategic alliances and goal-oriented networks. An implementation approach for value system alignment analysis is described, which is intended to assist managers in virtual and networked organizations management. The implementation of the assessment and analysis methods is supported by a set of software services integrated in the information system that supports the management of the networked organizations. A case study in the solar energy sector was conducted, and the data collected through this study allow us to confirm the practical applicability of the proposed methods and the software services.

  7. Static analysis of topology-dependent broadcast networks

    DEFF Research Database (Denmark)

    Nanz, Sebastian; Nielson, Flemming; Nielson, Hanne Riis

    2010-01-01

    changing network topology is a crucial ingredient. In this paper, we develop a static analysis that automatically constructs an abstract transition system, labelled by actions and connectivity information, to yield a mobility-preserving finite abstraction of the behaviour of a network expressed......Broadcast semantics poses significant challenges over point-to-point communication when it comes to formal modelling and analysis. Current approaches to analysing broadcast networks have focused on fixed connectivities, but this is unsuitable in the case of wireless networks where the dynamically...... in a process calculus with asynchronous local broadcast. Furthermore, we use model checking based on a 3-valued temporal logic to distinguish network behaviour which differs under changing connectivity patterns. (C) 2009 Elsevier Inc. All rights reserved....

  8. Performance Demonstration Program Plan for RCRA Constituent Analysis of Solidified Wastes

    International Nuclear Information System (INIS)

    2006-01-01

    The Performance Demonstration Program (PDP) for Resource Conservation and Recovery Act (RCRA) constituents distributes test samples for analysis of volatile organic compounds (VOCs), semivolatile organic compounds (SVOCs), and metals in solid matrices. Each distribution of test samples is termed a PDP cycle. These evaluation cycles provide an objective measure of the reliability of measurements performed for transuranic (TRU) waste characterization. The primary documents governing the conduct of the PDP are the Quality Assurance Program Document (QAPD; DOE/CBFO-94-1012) and the Waste Isolation Pilot Plant (WIPP) Waste Analysis Plan (WAP) contained in the Hazardous Waste Facility Permit (NM4890139088-TSDF) issued by the New Mexico Environment Department. The WAP requires participation in the PDP; the PDP must comply with the QAPD and the WAP. This plan implements the general requirements of the QAPD and the applicable requirements of the WAP for the RCRA PDP. Participating laboratories demonstrate acceptable performance by successfully analyzing single-blind performance evaluation samples (subsequently referred to as PDP samples) according to the criteria established in this plan. PDP samples are used as an independent means to assess laboratory performance regarding compliance with the WAP quality assurance objectives (QAOs). The concentrations of analytes in the PDP samples address levels of regulatory concern and encompass the range of concentrations anticipated in waste characterization samples. The WIPP requires analyses of homogeneous solid wastes to demonstrate compliance with regulatory requirements. These analyses must be performed by laboratories that demonstrate acceptable performance in this PDP. These analyses are referred to as WIPP analyses, and the samples on which they are performed are referred to as WIPP samples. Participating laboratories must analyze PDP samples using the same procedures used for WIPP samples.

  9. Trojan detection model based on network behavior analysis

    International Nuclear Information System (INIS)

    Liu Junrong; Liu Baoxu; Wang Wenjin

    2012-01-01

    Based on the analysis of existing Trojan detection technology, this paper presents a Trojan detection model based on network behavior analysis. First of all, we abstract description of the Trojan network behavior, then according to certain rules to establish the characteristic behavior library, and then use the support vector machine algorithm to determine whether a Trojan invasion. Finally, through the intrusion detection experiments, shows that this model can effectively detect Trojans. (authors)

  10. Network Analysis of Urban Traffic with Big Bus Data

    OpenAIRE

    Zhao, Kai

    2016-01-01

    Urban traffic analysis is crucial for traffic forecasting systems, urban planning and, more recently, various mobile and network applications. In this paper, we analyse urban traffic with network and statistical methods. Our analysis is based on one big bus dataset containing 45 million bus arrival samples in Helsinki. We mainly address following questions: 1. How can we identify the areas that cause most of the traffic in the city? 2. Why there is a urban traffic? Is bus traffic a key cause ...

  11. Classification and Analysis of Computer Network Traffic

    DEFF Research Database (Denmark)

    Bujlow, Tomasz

    2014-01-01

    various classification modes (decision trees, rulesets, boosting, softening thresholds) regarding the classification accuracy and the time required to create the classifier. We showed how to use our VBS tool to obtain per-flow, per-application, and per-content statistics of traffic in computer networks...

  12. Computer program for compressible flow network analysis

    Science.gov (United States)

    Wilton, M. E.; Murtaugh, J. P.

    1973-01-01

    Program solves problem of an arbitrarily connected one dimensional compressible flow network with pumping in the channels and momentum balancing at flow junctions. Program includes pressure drop calculations for impingement flow and flow through pin fin arrangements, as currently found in many air cooled turbine bucket and vane cooling configurations.

  13. Network Analysis with the Enron Email Corpus

    Science.gov (United States)

    Hardin, J. S.; Sarkis, G.; URC, P. .

    2015-01-01

    We use the Enron email corpus to study relationships in a network by applying six different measures of centrality. Our results came out of an in-semester undergraduate research seminar. The Enron corpus is well suited to statistical analyses at all levels of undergraduate education. Through this article's focus on centrality, students can explore…

  14. Using Citation Network Analysis in Educational Technology

    Science.gov (United States)

    Cho, Yonjoo; Park, Sunyoung

    2012-01-01

    Previous reviews in the field of Educational Technology (ET) have revealed some publication patterns according to authors, institutions, and affiliations. However, those previous reviews focused only on the rankings of individual authors and institutions, and did not provide qualitative details on relations and networks of scholars and scholarly…

  15. Analysis and Design of Complex Networks

    Science.gov (United States)

    2014-12-02

    systems. 08-NOV-10, . : , Barlas Oguz, Venkat Anantharam. Long range dependent Markov chains with applications , Information Theory and Applications ...JUL-12, . : , Michael Krishnan, Ehsan Haghani, Avideh Zakhor. Packet Length Adaptation in WLANs with Hidden Nodes and Time-Varying Channels, IEEE... WLAN networks with multi-antenna beam-forming nodes. VII. Use of busy/idle signals for discovering optimum AP association VIII

  16. AZ-101 Mixer Pump Demonstration and Tests Data Management Analysis Plan

    Energy Technology Data Exchange (ETDEWEB)

    DOUGLAS, D.G.

    2000-02-22

    This document provides a plan for the analysis of the data collected during the AZ-101 Mixer Pump Demonstration and Tests. This document was prepared after a review of the AZ-101 Mixer Pump Test Plan (Revision 4) [1] and other materials. The plan emphasizes a structured and well-ordered approach towards handling and examining the data. This plan presumes that the data will be collected and organized into a unified body of data, well annotated and bearing the date and time of each record. The analysis of this data will follow a methodical series of steps that are focused on well-defined objectives. Section 2 of this plan describes how the data analysis will proceed from the real-time monitoring of some of the key sensor data to the final analysis of the three-dimensional distribution of suspended solids. This section also identifies the various sensors or sensor systems and associates them with the various functions they serve during the test program. Section 3 provides an overview of the objectives of the AZ-101 test program and describes the data that will be analyzed to support that test. The objectives are: (1) to demonstrate that the mixer pumps can be operated within the operating requirements; (2) to demonstrate that the mixer pumps can mobilize the sludge in sufficient quantities to provide feed to the private contractor facility, and (3) to determine if the in-tank instrumentation is sufficient to monitor sludge mobilization and mixer pump operation. Section 3 also describes the interim analysis that organizes the data during the test, so the analysis can be more readily accomplished. Section 4 describes the spatial orientation of the various sensors in the tank. This section is useful in visualizing the relationship of the Sensors in terms of their location in the tank and how the data from these sensors may be related to the data from other sensors. Section 5 provides a summary of the various analyses that will be performed on the data during the test

  17. AZ-101 Mixer Pump Demonstration and Tests: Data Management (Analysis) Plan

    International Nuclear Information System (INIS)

    DOUGLAS, D.G.

    2000-01-01

    This document provides a plan for the analysis of the data collected during the AZ-101 Mixer Pump Demonstration and Tests. This document was prepared after a review of the AZ-101 Mixer Pump Test Plan (Revision 4) [1] and other materials. The plan emphasizes a structured and well-ordered approach towards handling and examining the data. This plan presumes that the data will be collected and organized into a unified body of data, well annotated and bearing the date and time of each record. The analysis of this data will follow a methodical series of steps that are focused on well-defined objectives. Section 2 of this plan describes how the data analysis will proceed from the real-time monitoring of some of the key sensor data to the final analysis of the three-dimensional distribution of suspended solids. This section also identifies the various sensors or sensor systems and associates them with the various functions they serve during the test program. Section 3 provides an overview of the objectives of the AZ-101 test program and describes the data that will be analyzed to support that test. The objectives are: (1) to demonstrate that the mixer pumps can be operated within the operating requirements; (2) to demonstrate that the mixer pumps can mobilize the sludge in sufficient quantities to provide feed to the private contractor facility, and (3) to determine if the in-tank instrumentation is sufficient to monitor sludge mobilization and mixer pump operation. Section 3 also describes the interim analysis that organizes the data during the test, so the analysis can be more readily accomplished. Section 4 describes the spatial orientation of the various sensors in the tank. This section is useful in visualizing the relationship of the Sensors in terms of their location in the tank and how the data from these sensors may be related to the data from other sensors. Section 5 provides a summary of the various analyses that will be performed on the data during the test

  18. Abnormal brain white matter network in young smokers: a graph theory analysis study.

    Science.gov (United States)

    Zhang, Yajuan; Li, Min; Wang, Ruonan; Bi, Yanzhi; Li, Yangding; Yi, Zhang; Liu, Jixin; Yu, Dahua; Yuan, Kai

    2018-04-01

    Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in some specific fiber bundles in smokers. However, little is known about the changes in topological organization of WM structural network in young smokers. In current study, we acquired DTI datasets from 58 male young smokers and 51 matched nonsmokers and constructed the WM networks by the deterministic fiber tracking approach. Graph theoretical analysis was used to compare the topological parameters of WM network (global and nodal) and the inter-regional fractional anisotropy (FA) weighted WM connections between groups. The results demonstrated that both young smokers and nonsmokers had small-world topology in WM network. Further analysis revealed that the young smokers exhibited the abnormal topological organization, i.e., increased network strength, global efficiency, and decreased shortest path length. In addition, the increased nodal efficiency predominately was located in frontal cortex, striatum and anterior cingulate gyrus (ACG) in smokers. Moreover, based on network-based statistic (NBS) approach, the significant increased FA-weighted WM connections were mainly found in the PFC, ACG and supplementary motor area (SMA) regions. Meanwhile, the network parameters were correlated with the nicotine dependence severity (FTND) scores, and the nodal efficiency of orbitofrontal cortex was positive correlation with the cigarette per day (CPD) in young smokers. We revealed the abnormal topological organization of WM network in young smokers, which may improve our understanding of the neural mechanism of young smokers form WM topological organization level.

  19. Robust neural network with applications to credit portfolio data analysis.

    Science.gov (United States)

    Feng, Yijia; Li, Runze; Sudjianto, Agus; Zhang, Yiyun

    2010-01-01

    In this article, we study nonparametric conditional quantile estimation via neural network structure. We proposed an estimation method that combines quantile regression and neural network (robust neural network, RNN). It provides good smoothing performance in the presence of outliers and can be used to construct prediction bands. A Majorization-Minimization (MM) algorithm was developed for optimization. Monte Carlo simulation study is conducted to assess the performance of RNN. Comparison with other nonparametric regression methods (e.g., local linear regression and regression splines) in real data application demonstrate the advantage of the newly proposed procedure.

  20. Bayesian analysis of heat pipe life test data for reliability demonstration testing

    International Nuclear Information System (INIS)

    Bartholomew, R.J.; Martz, H.F.

    1985-01-01

    The demonstration testing duration requirements to establish a quantitative measure of assurance of expected lifetime for heat pipes was determined. The heat pipes are candidate devices for transporting heat generated in a nuclear reactor core to thermoelectric converters for use as a space-based electric power plant. A Bayesian analysis technique is employed, utilizing a limited Delphi survey, and a geometric mean accelerated test criterion involving heat pipe power (P) and temperature (T). Resulting calculations indicate considerable test savings can be achieved by employing the method, but development testing to determine heat pipe failure mechanisms should not be circumvented

  1. Performance-Based Technology Selection Filter description report. INEL Buried Waste Integrated Demonstration System Analysis project

    Energy Technology Data Exchange (ETDEWEB)

    O`Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

    1992-05-01

    A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL).

  2. Functional Interaction Network Construction and Analysis for Disease Discovery.

    Science.gov (United States)

    Wu, Guanming; Haw, Robin

    2017-01-01

    Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

  3. atBioNet– an integrated network analysis tool for genomics and biomarker discovery

    Directory of Open Access Journals (Sweden)

    Ding Yijun

    2012-07-01

    Full Text Available Abstract Background Large amounts of mammalian protein-protein interaction (PPI data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. Results atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks. The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. Conclusion atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http

  4. atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

    Science.gov (United States)

    Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

    2012-07-20

    Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

  5. Network-assisted crop systems genetics: network inference and integrative analysis.

    Science.gov (United States)

    Lee, Tak; Kim, Hyojin; Lee, Insuk

    2015-04-01

    Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Performance assessment of air quality monitoring networks using principal component analysis and cluster analysis

    International Nuclear Information System (INIS)

    Lu, Wei-Zhen; He, Hong-Di; Dong, Li-yun

    2011-01-01

    This study aims to evaluate the performance of two statistical methods, principal component analysis and cluster analysis, for the management of air quality monitoring network of Hong Kong and the reduction of associated expenses. The specific objectives include: (i) to identify city areas with similar air pollution behavior; and (ii) to locate emission sources. The statistical methods were applied to the mass concentrations of sulphur dioxide (SO 2 ), respirable suspended particulates (RSP) and nitrogen dioxide (NO 2 ), collected in monitoring network of Hong Kong from January 2001 to December 2007. The results demonstrate that, for each pollutant, the monitoring stations are grouped into different classes based on their air pollution behaviors. The monitoring stations located in nearby area are characterized by the same specific air pollution characteristics and suggested with an effective management of air quality monitoring system. The redundant equipments should be transferred to other monitoring stations for allowing further enlargement of the monitored area. Additionally, the existence of different air pollution behaviors in the monitoring network is explained by the variability of wind directions across the region. The results imply that the air quality problem in Hong Kong is not only a local problem mainly from street-level pollutions, but also a region problem from the Pearl River Delta region. (author)

  7. Reliability analysis of cluster-based ad-hoc networks

    International Nuclear Information System (INIS)

    Cook, Jason L.; Ramirez-Marquez, Jose Emmanuel

    2008-01-01

    The mobile ad-hoc wireless network (MAWN) is a new and emerging network scheme that is being employed in a variety of applications. The MAWN varies from traditional networks because it is a self-forming and dynamic network. The MAWN is free of infrastructure and, as such, only the mobile nodes comprise the network. Pairs of nodes communicate either directly or through other nodes. To do so, each node acts, in turn, as a source, destination, and relay of messages. The virtue of a MAWN is the flexibility this provides; however, the challenge for reliability analyses is also brought about by this unique feature. The variability and volatility of the MAWN configuration makes typical reliability methods (e.g. reliability block diagram) inappropriate because no single structure or configuration represents all manifestations of a MAWN. For this reason, new methods are being developed to analyze the reliability of this new networking technology. New published methods adapt to this feature by treating the configuration probabilistically or by inclusion of embedded mobility models. This paper joins both methods together and expands upon these works by modifying the problem formulation to address the reliability analysis of a cluster-based MAWN. The cluster-based MAWN is deployed in applications with constraints on networking resources such as bandwidth and energy. This paper presents the problem's formulation, a discussion of applicable reliability metrics for the MAWN, and illustration of a Monte Carlo simulation method through the analysis of several example networks

  8. Optimization of deformation monitoring networks using finite element strain analysis

    Science.gov (United States)

    Alizadeh-Khameneh, M. Amin; Eshagh, Mehdi; Jensen, Anna B. O.

    2018-04-01

    An optimal design of a geodetic network can fulfill the requested precision and reliability of the network, and decrease the expenses of its execution by removing unnecessary observations. The role of an optimal design is highlighted in deformation monitoring network due to the repeatability of these networks. The core design problem is how to define precision and reliability criteria. This paper proposes a solution, where the precision criterion is defined based on the precision of deformation parameters, i. e. precision of strain and differential rotations. A strain analysis can be performed to obtain some information about the possible deformation of a deformable object. In this study, we split an area into a number of three-dimensional finite elements with the help of the Delaunay triangulation and performed the strain analysis on each element. According to the obtained precision of deformation parameters in each element, the precision criterion of displacement detection at each network point is then determined. The developed criterion is implemented to optimize the observations from the Global Positioning System (GPS) in Skåne monitoring network in Sweden. The network was established in 1989 and straddled the Tornquist zone, which is one of the most active faults in southern Sweden. The numerical results show that 17 out of all 21 possible GPS baseline observations are sufficient to detect minimum 3 mm displacement at each network point.

  9. Graph analysis of cell clusters forming vascular networks

    Science.gov (United States)

    Alves, A. P.; Mesquita, O. N.; Gómez-Gardeñes, J.; Agero, U.

    2018-03-01

    This manuscript describes the experimental observation of vasculogenesis in chick embryos by means of network analysis. The formation of the vascular network was observed in the area opaca of embryos from 40 to 55 h of development. In the area opaca endothelial cell clusters self-organize as a primitive and approximately regular network of capillaries. The process was observed by bright-field microscopy in control embryos and in embryos treated with Bevacizumab (Avastin), an antibody that inhibits the signalling of the vascular endothelial growth factor (VEGF). The sequence of images of the vascular growth were thresholded, and used to quantify the forming network in control and Avastin-treated embryos. This characterization is made by measuring vessels density, number of cell clusters and the largest cluster density. From the original images, the topology of the vascular network was extracted and characterized by means of the usual network metrics such as: the degree distribution, average clustering coefficient, average short path length and assortativity, among others. This analysis allows to monitor how the largest connected cluster of the vascular network evolves in time and provides with quantitative evidence of the disruptive effects that Avastin has on the tree structure of vascular networks.

  10. Improving Your Exploratory Factor Analysis for Ordinal Data: A Demonstration Using FACTOR

    Directory of Open Access Journals (Sweden)

    James Baglin

    2014-06-01

    Full Text Available Exploratory factor analysis (EFA methods are used extensively in the field of assessment and evaluation. Due to EFA's widespread use, common methods and practices have come under close scrutiny. A substantial body of literature has been compiled highlighting problems with many of the methods and practices used in EFA, and, in response, many guidelines have been proposed with the aim to improve application. Unfortunately, implementing recommended EFA practices has been restricted by the range of options available in commercial statistical packages and, perhaps, due to an absence of clear, practical - how-to' demonstrations. Consequently, this article describes the application of methods recommended to get the most out of your EFA. The article focuses on dealing with the common situation of analysing ordinal data as derived from Likert-type scales. These methods are demonstrated using the free, stand-alone, easy-to-use and powerful EFA package FACTOR (http://psico.fcep.urv.es/utilitats/factor/, Lorenzo-Seva & Ferrando, 2006. The demonstration applies the recommended techniques using an accompanying dataset, based on the Big 5 personality test. The outcomes obtained by the EFA using the recommended procedures through FACTOR are compared to the default techniques currently available in SPSS.

  11. Detecting Network Communities: An Application to Phylogenetic Analysis

    Science.gov (United States)

    Andrade, Roberto F. S.; Rocha-Neto, Ivan C.; Santos, Leonardo B. L.; de Santana, Charles N.; Diniz, Marcelo V. C.; Lobão, Thierry Petit; Goés-Neto, Aristóteles; Pinho, Suani T. R.; El-Hani, Charbel N.

    2011-01-01

    This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis. PMID:21573202

  12. System analysis and planning of a gas distribution network

    Energy Technology Data Exchange (ETDEWEB)

    Salas, Edwin F.M.; Farias, Helio Monteiro [AUTOMIND, Rio de Janeiro, RJ (Brazil); Costa, Carla V.R. [Universidade Salvador (UNIFACS), BA (Brazil)

    2009-07-01

    The increase in demand by gas consumers require that projects or improvements in gas distribution networks be made carefully and safely to ensure a continuous, efficient and economical supply. Gas distribution companies must ensure that the networks and equipment involved are defined and designed at the appropriate time to attend to the demands of the market. To do that a gas distribution network analysis and planning tool should use distribution networks and transmission models for the current situation and the future changes to be implemented. These models are used to evaluate project options and help in making appropriate decisions in order to minimize the capital investment in new components or simple changes in operational procedures. Gas demands are increasing and it is important that gas distribute design new distribution systems to ensure this growth, considering financial constraints of the company, as well as local legislation and regulation. In this study some steps of developing a flexible system that attends to those needs will be described. The analysis of distribution requires geographically referenced data for the models as well as an accurate connectivity and the attributes of the equipment. GIS systems are often used as a deposit center that holds the majority of this information. GIS systems are constantly updated as distribution network equipment is modified. The distribution network modeling gathered from this system ensures that the model represents the current network condition. The benefits of this architecture drastically reduce the creation and maintenance cost of the network models, because network components data are conveniently made available to populate the distribution network. This architecture ensures that the models are continually reflecting the reality of the distribution network. (author)

  13. Analysis and logical modeling of biological signaling transduction networks

    Science.gov (United States)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  14. A systematic review protocol: social network analysis of tobacco use.

    Science.gov (United States)

    Maddox, Raglan; Davey, Rachel; Lovett, Ray; van der Sterren, Anke; Corbett, Joan; Cochrane, Tom

    2014-08-08

    Tobacco use is the single most preventable cause of death in the world. Evidence indicates that behaviours such as tobacco use can influence social networks, and that social network structures can influence behaviours. Social network analysis provides a set of analytic tools to undertake methodical analysis of social networks. We will undertake a systematic review to provide a comprehensive synthesis of the literature regarding social network analysis and tobacco use. The review will answer the following research questions: among participants who use tobacco, does social network structure/position influence tobacco use? Does tobacco use influence peer selection? Does peer selection influence tobacco use? We will follow the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines and search the following databases for relevant articles: CINAHL (Cumulative Index to Nursing and Allied Health Literature); Informit Health Collection; PsycINFO; PubMed/MEDLINE; Scopus/Embase; Web of Science; and the Wiley Online Library. Keywords include tobacco; smoking; smokeless; cigarettes; cigar and 'social network' and reference lists of included articles will be hand searched. Studies will be included that provide descriptions of social network analysis of tobacco use.Qualitative, quantitative and mixed method data that meets the inclusion criteria for the review, including methodological rigour, credibility and quality standards, will be synthesized using narrative synthesis. Results will be presented using outcome statistics that address each of the research questions. This systematic review will provide a timely evidence base on the role of social network analysis of tobacco use, forming a basis for future research, policy and practice in this area. This systematic review will synthesise the evidence, supporting the hypothesis that social network structures can influence tobacco use. This will also include exploring the relationship between social

  15. Network Analysis of Commuting Flows: A Comparative Static Approach to German Data

    NARCIS (Netherlands)

    Patuelli, R.; Reggiani, A.; Nijkamp, P.; Bade, F-J

    2007-01-01

    The analysis of complex networks has recently received considerable attention. The work by Albert and Barabási presented a research challenge to network analysis, that is, growth of the network. The present paper offers a network analysis of the spatial commuting network in Germany. First, we study

  16. Meta-analytically informed network analysis of resting state FMRI reveals hyperconnectivity in an introspective socio-affective network in depression.

    Directory of Open Access Journals (Sweden)

    Leonhard Schilbach

    Full Text Available Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.

  17. Investment Valuation Analysis with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Hüseyin İNCE

    2017-07-01

    Full Text Available This paper shows that discounted cash flow and net present value, which are traditional investment valuation models, can be combined with artificial neural network model forecasting. The main inputs for the valuation models, such as revenue, costs, capital expenditure, and their growth rates, are heavily related to sector dynamics and macroeconomics. The growth rates of those inputs are related to inflation and exchange rates. Therefore, predicting inflation and exchange rates is a critical issue for the valuation output. In this paper, the Turkish economy’s inflation rate and the exchange rate of USD/TRY are forecast by artificial neural networks and implemented to the discounted cash flow model. Finally, the results are benchmarked with conventional practices.

  18. Network Configuration Analysis for Formation Flying Satellites

    Science.gov (United States)

    Knoblock, Eric J.; Wallett, Thomas M.; Konangi, Vijay K.; Bhasin, Kul B.

    2001-01-01

    The performance of two networks to support autonomous multi-spacecraft formation flying systems is presented. Both systems are comprised of a ten-satellite formation, with one of the satellites designated as the central or 'mother ship.' All data is routed through the mother ship to the terrestrial network. The first system uses a TCP/EP over ATM protocol architecture within the formation, and the second system uses the IEEE 802.11 protocol architecture within the formation. The simulations consist of file transfers using either the File Transfer Protocol (FTP) or the Simple Automatic File Exchange (SAFE) Protocol. The results compare the IP queuing delay, IP queue size and IP processing delay at the mother ship as well as end-to-end delay for both systems. In all cases, using IEEE 802.11 within the formation yields less delay. Also, the throughput exhibited by SAFE is better than FTP.

  19. Measurements and analysis of online social networks

    OpenAIRE

    González Sánchez, Roberto

    2014-01-01

    Mención Internacional Online Social Networks (OSNs) have become the most used Internet applications attracting hundreds of millions active users every day. The large amount of valuable information in OSNs (not even before available) has attracted the research community to design sophisticated techniques to collect, process, interpret and apply these data into a large range of disciplines including Sociology, Marketing, Computer Science, etc. This thesis presents a series of ...

  20. Analysis and design of networked control systems

    CERN Document Server

    You, Keyou; Xie, Lihua

    2015-01-01

    This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: ·         minimum data rate for stabilization of linear systems over noisy channels; ·         minimum network requirement for stabilization of linear systems over fading channels; and ·         stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are de...

  1. Qualitative Analysis of Commercial Social Network Profiles

    Science.gov (United States)

    Melendez, Lester; Wolfson, Ouri; Adjouadi, Malek; Rishe, Naphtali

    Social-networking sites have become an integral part of many users' daily internet routine. Commercial enterprises have been quick to recognize this and are subsequently creating profiles for many of their products and services. Commercial enterprises use social network profiles to target and interact with potential customers as well as to provide a gateway for users of the product or service to interact with each other. Many commercial enterprises use the statistics from their product or service's social network profile to tout the popularity and success of the product or service being showcased. They will use statistics such as number of friends, number of daily visits, number of interactions, and other similar measurements to quantify their claims. These statistics are often not a clear indication of the true popularity and success of the product. In this chapter the term product is used to refer to any tangible or intangible product, service, celebrity, personality, film, book, or other entity produced by a commercial enterprise.

  2. Network analysis: An innovative framework for understanding eating disorder psychopathology.

    Science.gov (United States)

    Smith, Kathryn E; Crosby, Ross D; Wonderlich, Stephen A; Forbush, Kelsie T; Mason, Tyler B; Moessner, Markus

    2018-03-01

    Network theory and analysis is an emerging approach in psychopathology research that has received increasing attention across fields of study. In contrast to medical models or latent variable approaches, network theory suggests that psychiatric syndromes result from systems of causal and reciprocal symptom relationships. Despite the promise of this approach to elucidate key mechanisms contributing to the development and maintenance of eating disorders (EDs), thus far, few applications of network analysis have been tested in ED samples. We first present an overview of network theory, review the existing findings in the ED literature, and discuss the limitations of this literature to date. In particular, the reliance on cross-sectional designs, use of single-item self-reports of symptoms, and instability of results have raised concern about the inferences that can be made from network analyses. We outline several areas to address in future ED network analytic research, which include the use of prospective designs and adoption of multimodal assessment methods. Doing so will provide a clearer understanding of whether network analysis can enhance our current understanding of ED psychopathology and inform clinical interventions. © 2018 Wiley Periodicals, Inc.

  3. Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

    Science.gov (United States)

    Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

    2016-01-01

    Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

  4. Evidence for anomalous network connectivity during working memory encoding in schizophrenia: an ICA based analysis.

    Directory of Open Access Journals (Sweden)

    Shashwath A Meda

    2009-11-01

    Full Text Available Numerous neuroimaging studies report abnormal regional brain activity during working memory performance in schizophrenia, but few have examined brain network integration as determined by "functional connectivity" analyses.We used independent component analysis (ICA to identify and characterize dysfunctional spatiotemporal networks in schizophrenia engaged during the different stages (encoding and recognition of a Sternberg working memory fMRI paradigm. 37 chronic schizophrenia and 54 healthy age/gender-matched participants performed a modified Sternberg Item Recognition fMRI task. Time series images preprocessed with SPM2 were analyzed using ICA. Schizophrenia patients showed relatively less engagement of several distinct "normal" encoding-related working memory networks compared to controls. These encoding networks comprised 1 left posterior parietal-left dorsal/ventrolateral prefrontal cortex, cingulate, basal ganglia, 2 right posterior parietal, right dorsolateral prefrontal cortex and 3 default mode network. In addition, the left fronto-parietal network demonstrated a load-dependent functional response during encoding. Network engagement that differed between groups during recognition comprised the posterior cingulate, cuneus and hippocampus/parahippocampus. As expected, working memory task accuracy differed between groups (p<0.0001 and was associated with degree of network engagement. Functional connectivity within all three encoding-associated functional networks correlated significantly with task accuracy, which further underscores the relevance of abnormal network integration to well-described schizophrenia working memory impairment. No network was significantly associated with task accuracy during the recognition phase.This study extends the results of numerous previous schizophrenia studies that identified isolated dysfunctional brain regions by providing evidence of disrupted schizophrenia functional connectivity using ICA within

  5. Cross Deployment Networking and Systematic Performance Analysis of Underwater Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhengxian Wei

    2017-07-01

    Full Text Available Underwater wireless sensor networks (UWSNs have become a new hot research area. However, due to the work dynamics and harsh ocean environment, how to obtain an UWSN with the best systematic performance while deploying as few sensor nodes as possible and setting up self-adaptive networking is an urgent problem that needs to be solved. Consequently, sensor deployment, networking, and performance calculation of UWSNs are challenging issues, hence the study in this paper centers on this topic and three relevant methods and models are put forward. Firstly, the normal body-centered cubic lattice to cross body-centered cubic lattice (CBCL has been improved, and a deployment process and topology generation method are built. Then most importantly, a cross deployment networking method (CDNM for UWSNs suitable for the underwater environment is proposed. Furthermore, a systematic quar-performance calculation model (SQPCM is proposed from an integrated perspective, in which the systematic performance of a UWSN includes coverage, connectivity, durability and rapid-reactivity. Besides, measurement models are established based on the relationship between systematic performance and influencing parameters. Finally, the influencing parameters are divided into three types, namely, constraint parameters, device performance and networking parameters. Based on these, a networking parameters adjustment method (NPAM for optimized systematic performance of UWSNs has been presented. The simulation results demonstrate that the approach proposed in this paper is feasible and efficient in networking and performance calculation of UWSNs.

  6. Network Analysis Approach to Stroke Care and Assistance Provision: An Empirical Study

    Directory of Open Access Journals (Sweden)

    Szczygiel Nina

    2017-06-01

    Full Text Available To model and analyse stroke care and assistance provision in the Portuguese context from the network perspective. We used the network theory as a theoretical foundation for the study. The model proposed by Frey et al. (2006 was used to elicit and comprehend possible interactions and relations between organisations expected to be involved in the provision of care and assistance to stroke patients in their pathway to rehabilitation. Providers were identified and contacted to evaluate the nature and intensity of relationships. Network analysis was performed with the NodeXL software package. Analysis of 509 entities based on about 260 000 entries indicates that stroke care provision in the evaluated context is best captured in the coalition-collaboration setting, which appears to best demonstrate the character of the network. Information from analysis of the collaboration stage was not sufficient to determine the network dynamics. Application of the network theory to understand interorganisational dynamics of the complex health care context. Empirical validation of the model proposed by Frey et al. (2006 in terms of its operationalisation and the way it actually reflects the practical context. Examination and analysis of interorganisational relationships and its contribution to management of compound health care context involving actors from various sectors.

  7. Growth of cortical neuronal network in vitro: Modeling and analysis

    International Nuclear Information System (INIS)

    Lai, P.-Y.; Jia, L. C.; Chan, C. K.

    2006-01-01

    We present a detailed analysis and theoretical growth models to account for recent experimental data on the growth of cortical neuronal networks in vitro [Phys. Rev. Lett. 93, 088101 (2004)]. The experimentally observed synchronized firing frequency of a well-connected neuronal network is shown to be proportional to the mean network connectivity. The growth of the network is consistent with the model of an early enhanced growth of connection, but followed by a retarded growth once the synchronized cluster is formed. Microscopic models with dominant excluded volume interactions are consistent with the observed exponential decay of the mean connection probability as a function of the mean network connectivity. The biological implications of the growth model are also discussed

  8. Modeling and Analysis of New Products Diffusion on Heterogeneous Networks

    Directory of Open Access Journals (Sweden)

    Shuping Li

    2014-01-01

    Full Text Available We present a heterogeneous networks model with the awareness stage and the decision-making stage to explain the process of new products diffusion. If mass media is neglected in the decision-making stage, there is a threshold whether the innovation diffusion is successful or not, or else it is proved that the network model has at least one positive equilibrium. For networks with the power-law degree distribution, numerical simulations confirm analytical results, and also at the same time, by numerical analysis of the influence of the network structure and persuasive advertisements on the density of adopters, we give two different products propagation strategies for two classes of nodes in scale-free networks.

  9. Sovereign public debt crisis in Europe. A network analysis

    Science.gov (United States)

    Matesanz, David; Ortega, Guillermo J.

    2015-10-01

    In this paper we analyse the evolving network structure of the quarterly public debt-to-GDP ratio from 2000 to 2014. By applying tools and concepts coming from complex systems we study the effects of the global financial crisis over public debt network connections and communities. Two main results arise from this analysis: firstly, countries public debts tend to synchronize their evolution, increasing global connectivity in the network and dramatically decreasing the number of communities. Secondly, a disruption in previous structure is observed at the time of the shock, emerging a more centralized and less diversify network topological organization which might be more prone to suffer contagion effects. This last fact is evidenced by an increasing tendency in countries of similar level of public debt to be connected between them, which we have quantified by the network assortativity.

  10. Network clustering coefficient approach to DNA sequence analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gerhardt, Guenther J.L. [Universidade Federal do Rio Grande do Sul-Hospital de Clinicas de Porto Alegre, Rua Ramiro Barcelos 2350/sala 2040/90035-003 Porto Alegre (Brazil); Departamento de Fisica e Quimica da Universidade de Caxias do Sul, Rua Francisco Getulio Vargas 1130, 95001-970 Caxias do Sul (Brazil); Lemke, Ney [Programa Interdisciplinar em Computacao Aplicada, Unisinos, Av. Unisinos, 950, 93022-000 Sao Leopoldo, RS (Brazil); Corso, Gilberto [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, Campus Universitario, 59072 970 Natal, RN (Brazil)]. E-mail: corso@dfte.ufrn.br

    2006-05-15

    In this work we propose an alternative DNA sequence analysis tool based on graph theoretical concepts. The methodology investigates the path topology of an organism genome through a triplet network. In this network, triplets in DNA sequence are vertices and two vertices are connected if they occur juxtaposed on the genome. We characterize this network topology by measuring the clustering coefficient. We test our methodology against two main bias: the guanine-cytosine (GC) content and 3-bp (base pairs) periodicity of DNA sequence. We perform the test constructing random networks with variable GC content and imposed 3-bp periodicity. A test group of some organisms is constructed and we investigate the methodology in the light of the constructed random networks. We conclude that the clustering coefficient is a valuable tool since it gives information that is not trivially contained in 3-bp periodicity neither in the variable GC content.

  11. Experimental demonstration of an OpenFlow based software-defined optical network employing packet, fixed and flexible DWDM grid technologies on an international multi-domain testbed.

    Science.gov (United States)

    Channegowda, M; Nejabati, R; Rashidi Fard, M; Peng, S; Amaya, N; Zervas, G; Simeonidou, D; Vilalta, R; Casellas, R; Martínez, R; Muñoz, R; Liu, L; Tsuritani, T; Morita, I; Autenrieth, A; Elbers, J P; Kostecki, P; Kaczmarek, P

    2013-03-11

    Software defined networking (SDN) and flexible grid optical transport technology are two key technologies that allow network operators to customize their infrastructure based on application requirements and therefore minimizing the extra capital and operational costs required for hosting new applications. In this paper, for the first time we report on design, implementation & demonstration of a novel OpenFlow based SDN unified control plane allowing seamless operation across heterogeneous state-of-the-art optical and packet transport domains. We verify and experimentally evaluate OpenFlow protocol extensions for flexible DWDM grid transport technology along with its integration with fixed DWDM grid and layer-2 packet switching.

  12. Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.

    Science.gov (United States)

    Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

    2016-01-01

    Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

  13. Financial Analysis of Hastily-Formed Networks

    Science.gov (United States)

    2006-09-01

    high-profile 101 Elvik Rune , “Cost-benefit analysis of ambulance and rescue helicopters in Norway...Systems Acquisition and Program Management. Rune , Elvik, “Cost-benefit analysis of ambulance and rescue helicopters in Norway: reflections on

  14. Development and Analysis of a VANET Network

    OpenAIRE

    Corral Zapata, Adrian

    2017-01-01

    Se denomina red vehicular ad hoc (en inglés Vehicular Ad Hoc Network, VANET) a una red de comunicación inalámbrica para la transmisión de información entre vehículos y elementos de la infraestructura de la carretera. La tecnología utilizada se engloba dentro de los sistemas inteligentes de transporte (en inglés Intelligent Transport Systems, ITS). El objetivo principal de las redes de comunicación vehiculares son la transmisión de información útil entre los elementos presentes en la carretera...

  15. Social Network Analysis and Critical Realism

    DEFF Research Database (Denmark)

    Buch-Hansen, Hubert

    2014-01-01

    in relation to established philosophies of science. This article argues that there is a tension between applied and methods-oriented SNA studies, on the one hand, and those addressing the social-theoretical nature and implications of networks, on the other. The former, in many cases, exhibits positivist...... tendencies, whereas the latter incorporate a number of assumptions that are directly compatible with core critical realist views on the nature of social reality and knowledge. This article suggests that SNA may be detached from positivist social science and come to constitute a valuable instrument...... in the critical realist toolbox....

  16. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Jianhua Ni

    2016-08-01

    Full Text Available The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

  17. SNAP: A General Purpose Network Analysis and Graph Mining Library.

    Science.gov (United States)

    Leskovec, Jure; Sosič, Rok

    2016-10-01

    Large networks are becoming a widely used abstraction for studying complex systems in a broad set of disciplines, ranging from social network analysis to molecular biology and neuroscience. Despite an increasing need to analyze and manipulate large networks, only a limited number of tools are available for this task. Here, we describe Stanford Network Analysis Platform (SNAP), a general-purpose, high-performance system that provides easy to use, high-level operations for analysis and manipulation of large networks. We present SNAP functionality, describe its implementational details, and give performance benchmarks. SNAP has been developed for single big-memory machines and it balances the trade-off between maximum performance, compact in-memory graph representation, and the ability to handle dynamic graphs where nodes and edges are being added or removed over time. SNAP can process massive networks with hundreds of millions of nodes and billions of edges. SNAP offers over 140 different graph algorithms that can efficiently manipulate large graphs, calculate structural properties, generate regular and random graphs, and handle attributes and meta-data on nodes and edges. Besides being able to handle large graphs, an additional strength of SNAP is that networks and their attributes are fully dynamic, they can be modified during the computation at low cost. SNAP is provided as an open source library in C++ as well as a module in Python. We also describe the Stanford Large Network Dataset, a set of social and information real-world networks and datasets, which we make publicly available. The collection is a complementary resource to our SNAP software and is widely used for development and benchmarking of graph analytics algorithms.

  18. Studying Policy Transfer through the Lens of Social Network Analysis

    DEFF Research Database (Denmark)

    Staunæs, Dorthe; Brøgger, Katja; Steiner-Khamsi, Gita

    Studying Policy Transfer through the Lens of Social Network Analysis The panelists present the findings of a joint empirical research project carried out at Aarhus University (DPU/Copenhagen) and at Teachers College, Columbia University (New York). The research project succeeded to identify...... discursive networks of political stakeholders and policy advisors that were considered key actors in the Danish school reform. The research team investigated how these networks interrelate, change over time, and represent different constituents (government, academe, business), at times contradicting...... or collaborating with each other, respectively. Against the backdrop of globalization studies in comparative education, the research project attempted to identify borrowers, translators, and brokers of educational reform drawing on a complementary set of expertise from social network analysis methodology (Oren...

  19. Network analysis of oyster transcriptome revealed a cascade of cellular responses during recovery after heat shock.

    Directory of Open Access Journals (Sweden)

    Lingling Zhang

    Full Text Available Oysters, as a major group of marine bivalves, can tolerate a wide range of natural and anthropogenic stressors including heat stress. Recent studies have shown that oysters pretreated with heat shock can result in induced heat tolerance. A systematic study of cellular recovery from heat shock may provide insights into the mechanism of acquired thermal tolerance. In this study, we performed the first network analysis of oyster transcriptome by reanalyzing microarray data from a previous study. Network analysis revealed a cascade of cellular responses during oyster recovery after heat shock and identified responsive gene modules and key genes. Our study demonstrates the power of network analysis in a non-model organism with poor gene annotations, which can lead to new discoveries that go beyond the focus on individual genes.

  20. Performability indicators for the traffic analysis of wide area networks

    International Nuclear Information System (INIS)

    Tsopelas, Panagiotis; Platis, Agapios

    2003-01-01

    In connecting computing networks, reliability term is strongly related to the availability of connections of Wide Area networks (WANs) or Local Area networks (LANs). In this paper we will examine the network connections activity of a Greek University in order to provide two sources of information: The Quantity of Information Not Delivered (QIND) and the Information Flow Interruption (IFI). These indicators will provide us with the inference of information from observable characteristics of data flow(s), even when the data is encrypted or otherwise not directly available (traffic), which is lost due to failures or upgrades inside this network. The reliability analysis is obtained by collecting the network failures data (duration and frequency) and traffic (total and average) for a specified period of 1 year. It is assumed that the numerical analysis is based on the fact that the lifetime follows and exponential distribution (here as we are working on discrete time the distribution must be the geometric distribution). Hence a Markov chain model seems suitable for modelling the functioning of this system. An algorithm concentrates the results in a transition probability matrix and calculates the reward functions for the QIND/IFI indicators with the use of the power method. Finally, the application part provides an example of how final results can be used to evaluate the observed network

  1. Network meta-analysis of disconnected networks: How dangerous are random baseline treatment effects?

    Science.gov (United States)

    Béliveau, Audrey; Goring, Sarah; Platt, Robert W; Gustafson, Paul

    2017-12-01

    In network meta-analysis, the use of fixed baseline treatment effects (a priori independent) in a contrast-based approach is regularly preferred to the use of random baseline treatment effects (a priori dependent). That is because, often, there is not a need to model baseline treatment effects, which carry the risk of model misspecification. However, in disconnected networks, fixed baseline treatment effects do not work (unless extra assumptions are made), as there is not enough information in the data to update the prior distribution on the contrasts between disconnected treatments. In this paper, we investigate to what extent the use of random baseline treatment effects is dangerous in disconnected networks. We take 2 publicly available datasets of connected networks and disconnect them in multiple ways. We then compare the results of treatment comparisons obtained from a Bayesian contrast-based analysis of each disconnected network using random normally distributed and exchangeable baseline treatment effects to those obtained from a Bayesian contrast-based analysis of their initial connected network using fixed baseline treatment effects. For the 2 datasets considered, we found that the use of random baseline treatment effects in disconnected networks was appropriate. Because those datasets were not cherry-picked, there should be other disconnected networks that would benefit from being analyzed using random baseline treatment effects. However, there is also a risk for the normality and exchangeability assumption to be inappropriate in other datasets even though we have not observed this situation in our case study. We provide code, so other datasets can be investigated. Copyright © 2017 John Wiley & Sons, Ltd.

  2. Google matrix analysis of C.elegans neural network

    Energy Technology Data Exchange (ETDEWEB)

    Kandiah, V., E-mail: kandiah@irsamc.ups-tlse.fr; Shepelyansky, D.L., E-mail: dima@irsamc.ups-tlse.fr

    2014-05-01

    We study the structural properties of the neural network of the C.elegans (worm) from a directed graph point of view. The Google matrix analysis is used to characterize the neuron connectivity structure and node classifications are discussed and compared with physiological properties of the cells. Our results are obtained by a proper definition of neural directed network and subsequent eigenvector analysis which recovers some results of previous studies. Our analysis highlights particular sets of important neurons constituting the core of the neural system. The applications of PageRank, CheiRank and ImpactRank to characterization of interdependency of neurons are discussed.

  3. Google matrix analysis of C.elegans neural network

    International Nuclear Information System (INIS)

    Kandiah, V.; Shepelyansky, D.L.

    2014-01-01

    We study the structural properties of the neural network of the C.elegans (worm) from a directed graph point of view. The Google matrix analysis is used to characterize the neuron connectivity structure and node classifications are discussed and compared with physiological properties of the cells. Our results are obtained by a proper definition of neural directed network and subsequent eigenvector analysis which recovers some results of previous studies. Our analysis highlights particular sets of important neurons constituting the core of the neural system. The applications of PageRank, CheiRank and ImpactRank to characterization of interdependency of neurons are discussed.

  4. Demonstration of Mobile Auto-GPS for Large Scale Human Mobility Analysis

    Science.gov (United States)

    Horanont, Teerayut; Witayangkurn, Apichon; Shibasaki, Ryosuke

    2013-04-01

    The greater affordability of digital devices and advancement of positioning and tracking capabilities have presided over today's age of geospatial Big Data. Besides, the emergences of massive mobile location data and rapidly increase in computational capabilities open up new opportunities for modeling of large-scale urban dynamics. In this research, we demonstrate the new type of mobile location data called "Auto-GPS" and its potential use cases for urban applications. More than one million Auto-GPS mobile phone users in Japan have been observed nationwide in a completely anonymous form for over an entire year from August 2010 to July 2011 for this analysis. A spate of natural disasters and other emergencies during the past few years has prompted new interest in how mobile location data can help enhance our security, especially in urban areas which are highly vulnerable to these impacts. New insights gleaned from mining the Auto-GPS data suggest a number of promising directions of modeling human movement during a large-scale crisis. We question how people react under critical situation and how their movement changes during severe disasters. Our results demonstrate a case of major earthquake and explain how people who live in Tokyo Metropolitan and vicinity area behave and return home after the Great East Japan Earthquake on March 11, 2011.

  5. Bayesian probability analysis: a prospective demonstration of its clinical utility in diagnosing coronary disease

    International Nuclear Information System (INIS)

    Detrano, R.; Yiannikas, J.; Salcedo, E.E.; Rincon, G.; Go, R.T.; Williams, G.; Leatherman, J.

    1984-01-01

    One hundred fifty-four patients referred for coronary arteriography were prospectively studied with stress electrocardiography, stress thallium scintigraphy, cine fluoroscopy (for coronary calcifications), and coronary angiography. Pretest probabilities of coronary disease were determined based on age, sex, and type of chest pain. These and pooled literature values for the conditional probabilities of test results based on disease state were used in Bayes theorem to calculate posttest probabilities of disease. The results of the three noninvasive tests were compared for statistical independence, a necessary condition for their simultaneous use in Bayes theorem. The test results were found to demonstrate pairwise independence in patients with and those without disease. Some dependencies that were observed between the test results and the clinical variables of age and sex were not sufficient to invalidate application of the theorem. Sixty-eight of the study patients had at least one major coronary artery obstruction of greater than 50%. When these patients were divided into low-, intermediate-, and high-probability subgroups according to their pretest probabilities, noninvasive test results analyzed by Bayesian probability analysis appropriately advanced 17 of them by at least one probability subgroup while only seven were moved backward. Of the 76 patients without disease, 34 were appropriately moved into a lower probability subgroup while 10 were incorrectly moved up. We conclude that posttest probabilities calculated from Bayes theorem more accurately classified patients with and without disease than did pretest probabilities, thus demonstrating the utility of the theorem in this application

  6. An Analysis of Construction Accident Factors Based on Bayesian Network

    OpenAIRE

    Yunsheng Zhao; Jinyong Pei

    2013-01-01

    In this study, we have an analysis of construction accident factors based on bayesian network. Firstly, accidents cases are analyzed to build Fault Tree method, which is available to find all the factors causing the accidents, then qualitatively and quantitatively analyzes the factors with Bayesian network method, finally determines the safety management program to guide the safety operations. The results of this study show that bad condition of geological environment has the largest posterio...

  7. Analysis of organizational culture with social network models

    OpenAIRE

    Titov, S.

    2015-01-01

    Organizational culture is nowadays an object of numerous scientific papers. However, only marginal part of existing research attempts to use the formal models of organizational cultures. The lack of organizational culture models significantly limits the further research in this area and restricts the application of the theory to practice of organizational culture change projects. The article consists of general views on potential application of network models and social network analysis to th...

  8. Stability analysis for cellular neural networks with variable delays

    International Nuclear Information System (INIS)

    Zhang Qiang; Wei Xiaopeng; Xu Jin

    2006-01-01

    Some sufficient conditions for the global exponential stability of cellular neural networks with variable delay are obtained by means of a method based on delay differential inequality. The method, which does not make use of Lyapunov functionals, is simple and effective for the stability analysis of neural networks with delay. Some previously established results in the literature are shown to be special cases of the presented result

  9. Time analysis of interconnection network implemented on the honeycomb architecture

    Energy Technology Data Exchange (ETDEWEB)

    Milutinovic, D [Inst. Michael Pupin, Belgrade (Yugoslavia)

    1996-12-31

    Problems of time domains analysis of the mapping of interconnection networks for parallel processing on one form of uniform massively parallel architecture of the cellular type are considered. The results of time analysis are discussed. It is found that changing the technology results in changing the mapping rules. 17 refs.

  10. Artificial neural network for on-site quantitative analysis of soils using laser induced breakdown spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    El Haddad, J. [Univ. Bordeaux, LOMA, UMR 5798, F-33400 Talence (France); CNRS, LOMA, UMR 5798, F-33400 Talence (France); Villot-Kadri, M.; Ismaël, A.; Gallou, G. [IVEA Solution, Centre Scientifique d' Orsay, Bât 503, 91400 Orsay (France); Michel, K.; Bruyère, D.; Laperche, V. [BRGM, Service Métrologie, Monitoring et Analyse, 3 avenue Claude Guillemin, B.P 36009, 45060 Orléans Cedex (France); Canioni, L. [Univ. Bordeaux, LOMA, UMR 5798, F-33400 Talence (France); CNRS, LOMA, UMR 5798, F-33400 Talence (France); Bousquet, B., E-mail: bruno.bousquet@u-bordeaux1.fr [Univ. Bordeaux, LOMA, UMR 5798, F-33400 Talence (France); CNRS, LOMA, UMR 5798, F-33400 Talence (France)

    2013-01-01

    Nowadays, due to environmental concerns, fast on-site quantitative analyses of soils are required. Laser induced breakdown spectroscopy is a serious candidate to address this challenge and is especially well suited for multi-elemental analysis of heavy metals. However, saturation and matrix effects prevent from a simple treatment of the LIBS data, namely through a regular calibration curve. This paper details the limits of this approach and consequently emphasizes the advantage of using artificial neural networks well suited for non-linear and multi-variate calibration. This advanced method of data analysis is evaluated in the case of real soil samples and on-site LIBS measurements. The selection of the LIBS data as input data of the network is particularly detailed and finally, resulting errors of prediction lower than 20% for aluminum, calcium, copper and iron demonstrate the good efficiency of the artificial neural networks for on-site quantitative LIBS of soils. - Highlights: ► We perform on-site quantitative LIBS analysis of soil samples. ► We demonstrate that univariate analysis is not convenient. ► We exploit artificial neural networks for LIBS analysis. ► Spectral lines other than the ones from the analyte must be introduced.

  11. Artificial neural network for on-site quantitative analysis of soils using laser induced breakdown spectroscopy

    International Nuclear Information System (INIS)

    El Haddad, J.; Villot-Kadri, M.; Ismaël, A.; Gallou, G.; Michel, K.; Bruyère, D.; Laperche, V.; Canioni, L.; Bousquet, B.

    2013-01-01

    Nowadays, due to environmental concerns, fast on-site quantitative analyses of soils are required. Laser induced breakdown spectroscopy is a serious candidate to address this challenge and is especially well suited for multi-elemental analysis of heavy metals. However, saturation and matrix effects prevent from a simple treatment of the LIBS data, namely through a regular calibration curve. This paper details the limits of this approach and consequently emphasizes the advantage of using artificial neural networks well suited for non-linear and multi-variate calibration. This advanced method of data analysis is evaluated in the case of real soil samples and on-site LIBS measurements. The selection of the LIBS data as input data of the network is particularly detailed and finally, resulting errors of prediction lower than 20% for aluminum, calcium, copper and iron demonstrate the good efficiency of the artificial neural networks for on-site quantitative LIBS of soils. - Highlights: ► We perform on-site quantitative LIBS analysis of soil samples. ► We demonstrate that univariate analysis is not convenient. ► We exploit artificial neural networks for LIBS analysis. ► Spectral lines other than the ones from the analyte must be introduced

  12. Network analysis of PTSD symptoms following mass violence.

    Science.gov (United States)

    Sullivan, Connor P; Smith, Andrew J; Lewis, Michael; Jones, Russell T

    2018-01-01

    Network analysis is a useful tool for understanding how symptoms interact with one another to influence psychopathology. However, this analytic strategy has not been fully utilized in the PTSD field. The current study utilized network analysis to examine connectedness and strength among PTSD symptoms (employing both partial correlation and regression network analyses) among a community sample of students exposed to the 2007 Virginia Tech shootings. Respondents (N = 4,639) completed online surveys 3-4 months postshootings, with PTSD symptom severity measured via the Trauma Symptom Questionnaire. Data were analyzed via adaptive least absolute shrinkage and selection operator (LASSO) and relative importance networks, as well as Dijkstra's algorithm to identify the shortest path from each symptom to all other symptoms. Relative importance network analysis revealed that intrusive thoughts had the strongest influence on other symptoms (i.e., had many strong connections [highest outdegree]) while computing Dijkstra's algorithm indicated that anger produced the shortest path to all other symptoms (i.e., the strongest connections to all other symptoms). Findings suggest that anger or intrusion likely play a crucial role in the development and maintenance of PTSD (i.e., are more influential within the network than are other symptoms). (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  13. Transient analysis for PWR reactor core using neural networks predictors

    International Nuclear Information System (INIS)

    Gueray, B.S.

    2001-01-01

    In this study, transient analysis for a Pressurized Water Reactor core has been performed. A lumped parameter approximation is preferred for that purpose, to describe the reactor core together with mechanism which play an important role in dynamic analysis. The dynamic behavior of the reactor core during transients is analyzed considering the transient initiating events, wich are an essential part of Safety Analysis Reports. several transients are simulated based on the employed core model. Simulation results are in accord the physical expectations. A neural network is developed to predict the future response of the reactor core, in advance. The neural network is trained using the simulation results of a number of representative transients. Structure of the neural network is optimized by proper selection of transfer functions for the neurons. Trained neural network is used to predict the future responses following an early observation of the changes in system variables. Estimated behaviour using the neural network is in good agreement with the simulation results for various for types of transients. Results of this study indicate that the designed neural network can be used as an estimator of the time dependent behavior of the reactor core under transient conditions

  14. Application of neural networks to quantitative spectrometry analysis

    International Nuclear Information System (INIS)

    Pilato, V.; Tola, F.; Martinez, J.M.; Huver, M.

    1999-01-01

    Accurate quantitative analysis of complex spectra (fission and activation products), relies upon experts' knowledge. In some cases several hours, even days of tedious calculations are needed. This is because current software is unable to solve deconvolution problems when several rays overlap. We have shown that such analysis can be correctly handled by a neural network, and the procedure can be automated with minimum laboratory measurements for networks training, as long as all the elements of the analysed solution figure in the training set and provided that adequate scaling of input data is performed. Once the network has been trained, analysis is carried out in a few seconds. On submitting to a test between several well-known laboratories, where unknown quantities of 57 Co, 58 Co, 85 Sr, 88 Y, 131 I, 139 Ce, 141 Ce present in a sample had to be determined, the results yielded by our network classed it amongst the best. The method is described, including experimental device and measures, training set designing, relevant input parameters definition, input data scaling and networks training. Main results are presented together with a statistical model allowing networks error prediction

  15. Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

    Science.gov (United States)

    Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

    2016-10-06

    Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

  16. Bank-firm credit network in Japan: an analysis of a bipartite network.

    Science.gov (United States)

    Marotta, Luca; Miccichè, Salvatore; Fujiwara, Yoshi; Iyetomi, Hiroshi; Aoyama, Hideaki; Gallegati, Mauro; Mantegna, Rosario N

    2015-01-01

    We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms.

  17. Bank-Firm Credit Network in Japan: An Analysis of a Bipartite Network

    Science.gov (United States)

    Marotta, Luca; Miccichè, Salvatore; Fujiwara, Yoshi; Iyetomi, Hiroshi; Aoyama, Hideaki; Gallegati, Mauro; Mantegna, Rosario N.

    2015-01-01

    We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms. PMID:25933413

  18. A performance analysis of DS-CDMA and SCPC VSAT networks

    Science.gov (United States)

    Hayes, David P.; Ha, Tri T.

    1990-01-01

    Spread-spectrum and single-channel-per-carrier (SCPC) transmission techniques work well in very small aperture terminal (VSAT) networks for multiple-access purposes while allowing the earth station antennas to remain small. Direct-sequence code-division multiple-access (DS-CDMA) is the simplest spread-spectrum technique to use in a VSAT network since a frequency synthesizer is not required for each terminal. An examination is made of the DS-CDMA and SCPC Ku-band VSAT satellite systems for low-density (64-kb/s or less) communications. A method for improving the standardf link analysis of DS-CDMA satellite-switched networks by including certain losses is developed. The performance of 50-channel full mesh and star network architectures is analyzed. The selection of operating conditions producing optimum performance is demonstrated.

  19. Energy and exergy analysis of low temperature district heating network

    International Nuclear Information System (INIS)

    Li, Hongwei; Svendsen, Svend

    2012-01-01

    Low temperature district heating with reduced network supply and return temperature provides better match of the low quality building heating demand and the low quality heating supply from waste heat or renewable energy. In this paper, a hypothetical low temperature district heating network is designed to supply heating for 30 low energy detached residential houses. The network operational supply/return temperature is set as 55 °C/25 °C, which is in line with a pilot project carried out in Denmark. Two types of in-house substations are analyzed to supply the consumer domestic hot water demand. The space heating demand is supplied through floor heating in the bathroom and low temperature radiators in the rest of rooms. The network thermal and hydraulic conditions are simulated under steady state. A district heating network design and simulation code is developed to incorporate the network optimization procedure and the network simultaneous factor. Through the simulation, the overall system energy and exergy efficiencies are calculated and the exergy losses for the major district heating system components are identified. Based on the results, suggestions are given to further reduce the system energy/exergy losses and increase the quality match between the consumer heating demand and the district heating supply. -- Highlights: ► Exergy and energy analysis for low and medium temperature district heating systems. ► Different district heating network dimensioning methods are analyzed. ► Major exergy losses are identified in the district heating network and the in-house substations. ► Advantages to apply low temperature district heating are highlighted through exergy analysis. ► The influence of thermal by-pass on system exergy/energy performance is analyzed.

  20. Mobile networks for biometric data analysis

    CERN Document Server

    Madrid, Natividad; Seepold, Ralf; Orcioni, Simone

    2016-01-01

    This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and high user acceptance. It comprises the peer-reviewed papers from the international workshop on the subject that was held in Ancona, Italy, in October 2014 and featured sessions on ICT for health care, biometric data in automotive and home applications, embedded systems for biometric data analysis, biometric data analysis: EMG and ECG, and ICT for gait analysis. The background to the book is the challenge posed by the prevention and treatment of common, widespread chronic diseases in modern, aging societies. Capture of biometric data is a cornerstone for any analysis and treatment strategy. The latest advances in sensor technology allow accurate data measurement in a non-intrusive way, and in many cases it is necessary to provide online monitoring and real-time data capturing to support a patient’s prevention pl...

  1. Protocol design and analysis for cooperative wireless networks

    CERN Document Server

    Song, Wei; Jin, A-Long

    2017-01-01

    This book focuses on the design and analysis of protocols for cooperative wireless networks, especially at the medium access control (MAC) layer and for crosslayer design between the MAC layer and the physical layer. It highlights two main points that are often neglected in other books: energy-efficiency and spatial random distribution of wireless devices. Effective methods in stochastic geometry for the design and analysis of wireless networks are also explored. After providing a comprehensive review of existing studies in the literature, the authors point out the challenges that are worth further investigation. Then, they introduce several novel solutions for cooperative wireless network protocols that reduce energy consumption and address spatial random distribution of wireless nodes. For each solution, the book offers a clear system model and problem formulation, details of the proposed cooperative schemes, comprehensive performance analysis, and extensive numerical and simulation results that validate th...

  2. Vibration analysis in nuclear power plant using neural networks

    International Nuclear Information System (INIS)

    Loskiewicz-Buczak, A.; Alguindigue, I.E.

    1993-01-01

    Vibration monitoring of components in nuclear power plants has been used for a number of years. This technique involves the analysis of vibration data coming from vital components of the plant to detect features which reflect the operational state of machinery. The analysis leads to the identification of potential failures and their causes, and makes it possible to perform efficient preventive maintenance. This paper documents the authors' work on the design of a vibration monitoring methodology enhanced by neural network technology. This technology provides an attractive complement to traditional vibration analysis because of the potential of neural networks to handle data which may be distorted or noisy. This paper describes three neural networks-based methods for the automation of some of the activities related to motion and vibration monitoring in engineering systems

  3. Continuous assessment of land mapping accuracy at High Resolution from global networks of atmospheric and field observatories -concept and demonstration

    Science.gov (United States)

    Sicard, Pierre; Martin-lauzer, François-regis

    2017-04-01

    In the context of global climate change and adjustment/resilience policies' design and implementation, there is a need not only i. for environmental monitoring, e.g. through a range of Earth Observations (EO) land "products" but ii. for a precise assessment of uncertainties of the aforesaid information that feed environmental decision-making (to be introduced in the EO metadata) and also iii. for a perfect handing of the thresholds which help translate "environment tolerance limits" to match detected EO changes through ecosystem modelling. Uncertainties' insight means precision and accuracy's knowledge and subsequent ability of setting thresholds for change detection systems. Traditionally, the validation of satellite-derived products has taken the form of intensive field campaigns to sanction the introduction of data processors in Payload Data Ground Segments chains. It is marred by logistical challenges and cost issues, reason why it is complemented by specific surveys at ground-based monitoring sites which can provide near-continuous observations at a high temporal resolution (e.g. RadCalNet). Unfortunately, most of the ground-level monitoring sites, in the number of 100th or 1000th, which are part of wider observation networks (e.g. FLUXNET, NEON, IMAGINES) mainly monitor the state of the atmosphere and the radiation exchange at the surface, which are different to the products derived from EO data. In addition they are "point-based" compared to the EO cover to be obtained from Sentinel-2 or Sentinel-3. Yet, data from these networks, processed by spatial extrapolation models, are well-suited to the bottom-up approach and relevant to the validation of vegetation parameters' consistency (e.g. leaf area index, fraction of absorbed photosynthetically active radiation). Consistency means minimal errors on spatial and temporal gradients of EO products. Test of the procedure for land-cover products' consistency assessment with field measurements delivered by worldwide

  4. A network analysis of the Chinese stock market

    Science.gov (United States)

    Huang, Wei-Qiang; Zhuang, Xin-Tian; Yao, Shuang

    2009-07-01

    In many practical important cases, a massive dataset can be represented as a very large network with certain attributes associated with its vertices and edges. Stock markets generate huge amounts of data, which can be use for constructing the network reflecting the market’s behavior. In this paper, we use a threshold method to construct China’s stock correlation network and then study the network’s structural properties and topological stability. We conduct a statistical analysis of this network and show that it follows a power-law model. We also detect components, cliques and independent sets in this network. These analyses allows one to apply a new data mining technique of classifying financial instruments based on stock price data, which provides a deeper insight into the internal structure of the stock market. Moreover, we test the topological stability of this network and find that it displays a topological robustness against random vertex failures, but it is also fragile to intentional attacks. Such a network stability property would be also useful for portfolio investment and risk management.

  5. SOCIOLOGICAL UNDERSTANDING OF INTERNET: THEORETICAL APPROACHES TO THE NETWORK ANALYSIS

    Directory of Open Access Journals (Sweden)

    D. E. Dobrinskaya

    2016-01-01

    Full Text Available Internet studies are carried out by various scientific disciplines and in different research perspectives. Sociological studies of the Internet deal with a new technology, a revolutionary means of mass communication and a social space. There is a set of research difficulties associated with the Internet. Firstly, the high speed and wide spread of Internet technologies’ development. Secondly, the collection and filtration of materials concerning with Internet studies. Lastly, the development of new conceptual categories, which are able to reflect the impact of the Internet development in contemporary world. In that regard the question of the “network” category use is essential. Network is the base of Internet functioning, on the one hand. On the other hand, network is the ground for almost all social interactions in modern society. So such society is called network society. Three theoretical network approaches in the Internet research case are the most relevant: network society theory, social network analysis and actor-network theory. Each of these theoretical approaches contributes to the study of the Internet. They shape various images of interactions between human beings in their entity and dynamics. All these approaches also provide information about the nature of these interactions. 

  6. Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis.

    Science.gov (United States)

    Caeyenberghs, K; Powell, H W R; Thomas, R H; Brindley, L; Church, C; Evans, J; Muthukumaraswamy, S D; Jones, D K; Hamandi, K

    2015-01-01

    Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients.

  7. Performance analysis for gait in camera networks

    OpenAIRE

    Michela Goffredo; Imed Bouchrika; John Carter; Mark Nixon

    2008-01-01

    This paper deploys gait analysis for subject identification in multi-camera surveillance scenarios. We present a new method for viewpoint independent markerless gait analysis that does not require camera calibration and works with a wide range of directions of walking. These properties make the proposed method particularly suitable for gait identification in real surveillance scenarios where people and their behaviour need to be tracked across a set of cameras. Tests on 300 synthetic and real...

  8. Neural network approach in multichannel auditory event-related potential analysis.

    Science.gov (United States)

    Wu, F Y; Slater, J D; Ramsay, R E

    1994-04-01

    Even though there are presently no clearly defined criteria for the assessment of P300 event-related potential (ERP) abnormality, it is strongly indicated through statistical analysis that such criteria exist for classifying control subjects and patients with diseases resulting in neuropsychological impairment such as multiple sclerosis (MS). We have demonstrated the feasibility of artificial neural network (ANN) methods in classifying ERP waveforms measured at a single channel (Cz) from control subjects and MS patients. In this paper, we report the results of multichannel ERP analysis and a modified network analysis methodology to enhance automation of the classification rule extraction process. The proposed methodology significantly reduces the work of statistical analysis. It also helps to standardize the criteria of P300 ERP assessment and facilitate the computer-aided analysis on neuropsychological functions.

  9. Temporal analysis of social networks using three-way DEDICOM.

    Energy Technology Data Exchange (ETDEWEB)

    Bader, Brett William; Harshman, Richard A. (University of Ontario, London, Ontario, Canada); Kolda, Tamara Gibson (Sandia National Laboratories, Livermore, CA)

    2006-06-01

    DEDICOM is an algebraic model for analyzing intrinsically asymmetric relationships, such as the balance of trade among nations or the flow of information among organizations or individuals. It provides information on latent components in the data that can be regarded as ''properties'' or ''aspects'' of the objects, and it finds a few patterns that can be combined to describe many relationships among these components. When we apply this technique to adjacency matrices arising from directed graphs, we obtain a smaller graph that gives an idealized description of its patterns. Three-way DEDICOM is a higher-order extension of the model that has certain uniqueness properties. It allows for a third mode of the data, such as time, and permits the analysis of semantic graphs. We present an improved algorithm for computing three-way DEDICOM on sparse data and demonstrate it by applying it to the adjacency tensor of a semantic graph with time-labeled edges. Our application uses the Enron email corpus, from which we construct a semantic graph corresponding to email exchanges among Enron personnel over a series of 44 months. Meaningful patterns are recovered in which the representation of asymmetries adds insight into the social networks at Enron.

  10. Formulation and demonstration of a robust mean variance optimization approach for concurrent airline network and aircraft design

    Science.gov (United States)

    Davendralingam, Navindran

    Conceptual design of aircraft and the airline network (routes) on which aircraft fly on are inextricably linked to passenger driven demand. Many factors influence passenger demand for various Origin-Destination (O-D) city pairs including demographics, geographic location, seasonality, socio-economic factors and naturally, the operations of directly competing airlines. The expansion of airline operations involves the identificaion of appropriate aircraft to meet projected future demand. The decisions made in incorporating and subsequently allocating these new aircraft to serve air travel demand affects the inherent risk and profit potential as predicted through the airline revenue management systems. Competition between airlines then translates to latent passenger observations of the routes served between OD pairs and ticket pricing---this in effect reflexively drives future states of demand. This thesis addresses the integrated nature of aircraft design, airline operations and passenger demand, in order to maximize future expected profits as new aircraft are brought into service. The goal of this research is to develop an approach that utilizes aircraft design, airline network design and passenger demand as a unified framework to provide better integrated design solutions in order to maximize expexted profits of an airline. This is investigated through two approaches. The first is a static model that poses the concurrent engineering paradigm above as an investment portfolio problem. Modern financial portfolio optimization techniques are used to leverage risk of serving future projected demand using a 'yet to be introduced' aircraft against potentially generated future profits. Robust optimization methodologies are incorporated to mitigate model sensitivity and address estimation risks associated with such optimization techniques. The second extends the portfolio approach to include dynamic effects of an airline's operations. A dynamic programming approach is

  11. The Reconstruction and Analysis of Gene Regulatory Networks.

    Science.gov (United States)

    Zheng, Guangyong; Huang, Tao

    2018-01-01

    In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

  12. Simulated, Emulated, and Physical Investigative Analysis (SEPIA) of networked systems.

    Energy Technology Data Exchange (ETDEWEB)

    Burton, David P.; Van Leeuwen, Brian P.; McDonald, Michael James; Onunkwo, Uzoma A.; Tarman, Thomas David; Urias, Vincent E.

    2009-09-01

    This report describes recent progress made in developing and utilizing hybrid Simulated, Emulated, and Physical Investigative Analysis (SEPIA) environments. Many organizations require advanced tools to analyze their information system's security, reliability, and resilience against cyber attack. Today's security analysis utilize real systems such as computers, network routers and other network equipment, computer emulations (e.g., virtual machines) and simulation models separately to analyze interplay between threats and safeguards. In contrast, this work developed new methods to combine these three approaches to provide integrated hybrid SEPIA environments. Our SEPIA environments enable an analyst to rapidly configure hybrid environments to pass network traffic and perform, from the outside, like real networks. This provides higher fidelity representations of key network nodes while still leveraging the scalability and cost advantages of simulation tools. The result is to rapidly produce large yet relatively low-cost multi-fidelity SEPIA networks of computers and routers that let analysts quickly investigate threats and test protection approaches.

  13. Hybrid modeling and empirical analysis of automobile supply chain network

    Science.gov (United States)

    Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying

    2017-05-01

    Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.

  14. SEDIMENT ANALYSIS NETWORK FOR DECISION SUPPORT (SANDS) LANDSAT GEOLOGICAL SURVEY OF AL (GSA) ANALYSIS V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Sediment Analysis Network for Decision Support (SANDS) Landsat Geological Survey of AL (GSA) Analysis dataset analyzed changes in the coastal shoreline and...

  15. UGV: security analysis of subsystem control network

    Science.gov (United States)

    Abbott-McCune, Sam; Kobezak, Philip; Tront, Joseph; Marchany, Randy; Wicks, Al

    2013-05-01

    Unmanned Ground vehicles (UGVs) are becoming prolific in the heterogeneous superset of robotic platforms. The sensors which provide odometry, localization, perception, and vehicle diagnostics are fused to give the robotic platform a sense of the environment it is traversing. The automotive industry CAN bus has dominated the industry due to the fault tolerance and the message structure allowing high priority messages to reach the desired node in a real time environment. UGVs are being researched and produced at an accelerated rate to preform arduous, repetitive, and dangerous missions that are associated with a military action in a protracted conflict. The technology and applications of the research will inevitably be turned into dual-use platforms to aid civil agencies in the performance of their various operations. Our motivation is security of the holistic system; however as subsystems are outsourced in the design, the overall security of the system may be diminished. We will focus on the CAN bus topology and the vulnerabilities introduced in UGVs and recognizable security vulnerabilities that are inherent in the communications architecture. We will show how data can be extracted from an add-on CAN bus that can be customized to monitor subsystems. The information can be altered or spoofed to force the vehicle to exhibit unwanted actions or render the UGV unusable for the designed mission. The military relies heavily on technology to maintain information dominance, and the security of the information introduced onto the network by UGVs must be safeguarded from vulnerabilities that can be exploited.

  16. Collective Competence and Social Capital Analysis in Collaborative Networks

    Directory of Open Access Journals (Sweden)

    Janaina Macke

    2010-06-01

    Full Text Available The present paper addresses the issue of collective competence and social capital analysis for collaborative networks. The objective of the project is to understand how collaborative networks can be influenced considering the perspective of social capital and core competences. In this model we defend the emphasis on endogenous resources, once the technology is, in a general way, accessible to most of the companies and, therefore will not be a long term competitive advantage. The model shows that collaborative networks will be more competitive and successful if they invest in to core elements that are: organizational culture and people. Therefore, the model contributes for the researches in socio-organizational filed and provides a tool to evaluate collaborative networks.

  17. Stochastic sensitivity analysis and Langevin simulation for neural network learning

    International Nuclear Information System (INIS)

    Koda, Masato

    1997-01-01

    A comprehensive theoretical framework is proposed for the learning of a class of gradient-type neural networks with an additive Gaussian white noise process. The study is based on stochastic sensitivity analysis techniques, and formal expressions are obtained for stochastic learning laws in terms of functional derivative sensitivity coefficients. The present method, based on Langevin simulation techniques, uses only the internal states of the network and ubiquitous noise to compute the learning information inherent in the stochastic correlation between noise signals and the performance functional. In particular, the method does not require the solution of adjoint equations of the back-propagation type. Thus, the present algorithm has the potential for efficiently learning network weights with significantly fewer computations. Application to an unfolded multi-layered network is described, and the results are compared with those obtained by using a back-propagation method

  18. Center of attention: A network text analysis of American Sniper

    Directory of Open Access Journals (Sweden)

    Starling Hunter

    2016-06-01

    Full Text Available Network Text Analysis (NTA is a term used to describe a variety of software - supported methods for modeling texts as networks of concepts. In this study we apply NTA to the screenplay of American Sniper, an Academy Award nominee for Best Adapted Screenplay in 2014. Specifically, we est ablish prior expectations as to the key themes associated with war films. We then empirically test whether words associated with the most influentially - positioned nodes in the network signify themes common to the war - film genre. As predicted, we find tha t words and concepts associated with the least constrained nodes in the text network were significantly more likely to be associated with the war genre and significantly less likely to be associated with genres to which the film did not belong.

  19. [Weighted gene co-expression network analysis in biomedicine research].

    Science.gov (United States)

    Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

    2017-11-25

    High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

  20. Heterogeneous Deployment Analysis for Cost-Effective Mobile Network Evolution

    DEFF Research Database (Denmark)

    Coletti, Claudio

    2013-01-01

    network coverage and boosting network capacity in traffic hot-spot areas. The thesis deals with the deployment of both outdoor small cells and indoor femto cells. Amongst the outdoor solution, particular emphasis is put on relay base stations as backhaul costs can be reduced by utilizing LTE spectrum...... statistical models of deployment areas, the performance analysis is carried out in the form of operator case studies for large-scale deployment scenarios, including realistic macro network layouts and inhomogeneous spatial traffic distributions. Deployment of small cells is performed by means of proposed...... heuristic deployment algorithms, which combine network coverage and spatial user density information. As a secondary aspect, deployment solutions achieving the same coverage performance are compared in terms of Total Cost of Ownership (TCO), in order to investigate the viability of different deployment...